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https://github.com/trustgraph-ai/trustgraph.git
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init
This commit is contained in:
elpresidank
parent
c386f68743
commit
b6536eca38
100 changed files with 17680 additions and 377 deletions
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@ -2,7 +2,7 @@
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* TrustGraph MCP server.
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*
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* Exposes TrustGraph capabilities as MCP tools for AI assistants.
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* Communicates with the TrustGraph gateway via WebSocket.
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* Uses the vendored @trustgraph/client for all gateway communication.
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*
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* Python reference: trustgraph-mcp/trustgraph/mcp_server/mcp.py
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*/
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@ -10,10 +10,11 @@
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import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
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import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
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import { z } from "zod";
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import { SocketManager } from "./socket-manager.js";
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import { createTrustGraphSocket, type BaseApi, type Term } from "@trustgraph/client";
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export function createMcpServer(config: {
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gatewayUrl: string;
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user?: string;
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token?: string;
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flowId?: string;
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}) {
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@ -22,13 +23,17 @@ export function createMcpServer(config: {
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version: "0.1.0",
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});
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const socket = new SocketManager({
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gatewayUrl: config.gatewayUrl,
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token: config.token,
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});
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const user = config.user ?? "mcp";
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const socket: BaseApi = createTrustGraphSocket(
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user,
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config.token,
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config.gatewayUrl,
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);
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const flowId = config.flowId ?? "default";
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// ===================== Flow-scoped tools =====================
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// --- Text Completion ---
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server.tool(
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"text_completion",
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@ -38,8 +43,9 @@ export function createMcpServer(config: {
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prompt: z.string().describe("User prompt"),
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},
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async ({ system, prompt }) => {
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const resp = await socket.request("text-completion", { system, prompt }, { flowId }) as Record<string, unknown>;
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return { content: [{ type: "text" as const, text: String(resp.response ?? resp) }] };
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const flow = socket.flow(flowId);
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const response = await flow.textCompletion(system, prompt);
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return { content: [{ type: "text" as const, text: response }] };
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},
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);
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@ -51,14 +57,32 @@ export function createMcpServer(config: {
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query: z.string().describe("Natural language query"),
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entity_limit: z.number().optional().describe("Max entities to retrieve"),
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triple_limit: z.number().optional().describe("Max triples per entity"),
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collection: z.string().optional().describe("Collection name"),
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},
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async ({ query, entity_limit, triple_limit }) => {
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const resp = await socket.request(
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"graph-rag",
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{ query, entity_limit, triple_limit },
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{ flowId },
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) as Record<string, unknown>;
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return { content: [{ type: "text" as const, text: String(resp.response ?? resp) }] };
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async ({ query, entity_limit, triple_limit, collection }) => {
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const flow = socket.flow(flowId);
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const response = await flow.graphRag(
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query,
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{ entityLimit: entity_limit, tripleLimit: triple_limit },
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collection,
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);
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return { content: [{ type: "text" as const, text: response }] };
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},
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);
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// --- Document RAG ---
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server.tool(
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"document_rag",
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"Query documents using RAG",
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{
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query: z.string().describe("Natural language query"),
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doc_limit: z.number().optional().describe("Max documents to retrieve"),
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collection: z.string().optional().describe("Collection name"),
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},
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async ({ query, doc_limit, collection }) => {
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const flow = socket.flow(flowId);
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const response = await flow.documentRag(query, doc_limit, collection);
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return { content: [{ type: "text" as const, text: response }] };
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},
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);
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@ -70,8 +94,23 @@ export function createMcpServer(config: {
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question: z.string().describe("Question for the agent"),
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},
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async ({ question }) => {
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const resp = await socket.request("agent", { question }, { flowId }) as Record<string, unknown>;
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return { content: [{ type: "text" as const, text: String(resp.answer ?? resp) }] };
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const flow = socket.flow(flowId);
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let fullAnswer = "";
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await new Promise<void>((resolve, reject) => {
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flow.agent(
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question,
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() => {}, // think — ignore for MCP
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() => {}, // observe — ignore for MCP
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(chunk, complete) => {
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fullAnswer += chunk;
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if (complete) resolve();
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},
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(err) => reject(new Error(err)),
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);
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});
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return { content: [{ type: "text" as const, text: fullAnswer }] };
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},
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);
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@ -83,8 +122,9 @@ export function createMcpServer(config: {
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text: z.array(z.string()).describe("Texts to embed"),
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},
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async ({ text }) => {
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const resp = await socket.request("embeddings", { text }, { flowId }) as Record<string, unknown>;
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return { content: [{ type: "text" as const, text: JSON.stringify(resp) }] };
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const flow = socket.flow(flowId);
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const vectors = await flow.embeddings(text);
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return { content: [{ type: "text" as const, text: JSON.stringify(vectors) }] };
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},
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);
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@ -97,15 +137,15 @@ export function createMcpServer(config: {
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p: z.string().optional().describe("Predicate IRI"),
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o: z.string().optional().describe("Object IRI or literal"),
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limit: z.number().optional().describe("Max results"),
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collection: z.string().optional().describe("Collection name"),
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},
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async ({ s, p, o, limit }) => {
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const request: Record<string, unknown> = { limit };
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if (s) request.s = { type: "IRI", iri: s };
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if (p) request.p = { type: "IRI", iri: p };
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if (o) request.o = { type: "IRI", iri: o };
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const resp = await socket.request("triples-query", request, { flowId }) as Record<string, unknown>;
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return { content: [{ type: "text" as const, text: JSON.stringify(resp, null, 2) }] };
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async ({ s, p, o, limit, collection }) => {
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const flow = socket.flow(flowId);
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const sTerm: Term | undefined = s ? { t: "i", i: s } : undefined;
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const pTerm: Term | undefined = p ? { t: "i", i: p } : undefined;
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const oTerm: Term | undefined = o ? { t: "i", i: o } : undefined;
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const triples = await flow.triplesQuery(sTerm, pTerm, oTerm, limit, collection);
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return { content: [{ type: "text" as const, text: JSON.stringify(triples, null, 2) }] };
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},
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);
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@ -116,28 +156,48 @@ export function createMcpServer(config: {
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{
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query: z.string().describe("Text to find similar entities for"),
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limit: z.number().optional().describe("Max results"),
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collection: z.string().optional().describe("Collection name"),
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},
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async ({ query, limit }) => {
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async ({ query, limit, collection }) => {
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const flow = socket.flow(flowId);
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// First embed the query, then search
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const embResp = await socket.request("embeddings", { text: [query] }, { flowId }) as { vectors: number[][] };
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const resp = await socket.request(
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"graph-embeddings-query",
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{ vectors: embResp.vectors, limit: limit ?? 10 },
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{ flowId },
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) as Record<string, unknown>;
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const vectors = await flow.embeddings([query]);
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const entities = await flow.graphEmbeddingsQuery(
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vectors[0],
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limit ?? 10,
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collection,
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);
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return { content: [{ type: "text" as const, text: JSON.stringify(entities, null, 2) }] };
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},
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);
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// ===================== Config tools =====================
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server.tool(
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"get_config_all",
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"Get all configuration values",
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{},
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async () => {
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const cfg = socket.config();
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const resp = await cfg.getConfigAll();
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return { content: [{ type: "text" as const, text: JSON.stringify(resp, null, 2) }] };
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},
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);
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// --- Config ---
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server.tool(
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"get_config",
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"Get configuration values",
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"Get specific configuration values",
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{
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keys: z.array(z.string()).describe("Config keys to retrieve"),
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keys: z.array(
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z.object({
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type: z.string().describe("Config type"),
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key: z.string().describe("Config key"),
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}),
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).describe("Config keys to retrieve"),
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},
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async ({ keys }) => {
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const resp = await socket.request("config", { operation: "get", keys }) as Record<string, unknown>;
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const cfg = socket.config();
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const resp = await cfg.getConfig(keys);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp, null, 2) }] };
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},
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);
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"put_config",
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"Set configuration values",
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{
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values: z.record(z.unknown()).describe("Key-value pairs to set"),
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values: z.array(
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z.object({
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type: z.string().describe("Config type"),
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key: z.string().describe("Config key"),
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value: z.string().describe("Config value (JSON-encoded)"),
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}),
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).describe("Key-value entries to set"),
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},
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async ({ values }) => {
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const resp = await socket.request("config", { operation: "put", values }) as Record<string, unknown>;
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const cfg = socket.config();
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const resp = await cfg.putConfig(values);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp) }] };
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},
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);
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server.tool(
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"delete_config",
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"Delete a configuration entry",
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{
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type: z.string().describe("Config type"),
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key: z.string().describe("Config key"),
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},
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async ({ type, key }) => {
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const cfg = socket.config();
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const resp = await cfg.deleteConfig({ type, key });
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return { content: [{ type: "text" as const, text: JSON.stringify(resp) }] };
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},
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);
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// ===================== Flow management tools =====================
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server.tool(
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"get_flows",
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"List all available flows",
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{},
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async () => {
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const flows = socket.flows();
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const ids = await flows.getFlows();
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return { content: [{ type: "text" as const, text: JSON.stringify(ids, null, 2) }] };
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},
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);
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server.tool(
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"get_flow",
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"Get a specific flow definition",
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{
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flow_id: z.string().describe("Flow ID to retrieve"),
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},
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async ({ flow_id }) => {
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const flows = socket.flows();
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const def = await flows.getFlow(flow_id);
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return { content: [{ type: "text" as const, text: JSON.stringify(def, null, 2) }] };
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},
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);
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server.tool(
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"start_flow",
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"Start a flow instance",
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{
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flow_id: z.string().describe("Flow ID"),
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blueprint_name: z.string().describe("Blueprint name"),
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description: z.string().describe("Flow description"),
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parameters: z.record(z.unknown()).optional().describe("Optional flow parameters"),
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},
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async ({ flow_id, blueprint_name, description, parameters }) => {
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const flows = socket.flows();
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const resp = await flows.startFlow(flow_id, blueprint_name, description, parameters);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp, null, 2) }] };
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},
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);
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server.tool(
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"stop_flow",
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"Stop a running flow",
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{
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flow_id: z.string().describe("Flow ID to stop"),
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},
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async ({ flow_id }) => {
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const flows = socket.flows();
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const resp = await flows.stopFlow(flow_id);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp, null, 2) }] };
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},
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);
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// ===================== Library (document) tools =====================
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server.tool(
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"get_documents",
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"List all documents in the library",
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{},
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async () => {
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const lib = socket.librarian();
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const docs = await lib.getDocuments();
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return { content: [{ type: "text" as const, text: JSON.stringify(docs, null, 2) }] };
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},
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);
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server.tool(
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"load_document",
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"Upload a document to the library",
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{
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document: z.string().describe("Base64-encoded document content"),
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mime_type: z.string().describe("Document MIME type"),
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title: z.string().describe("Document title"),
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comments: z.string().optional().describe("Additional comments"),
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tags: z.array(z.string()).optional().describe("Document tags"),
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id: z.string().optional().describe("Optional document ID"),
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},
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async ({ document, mime_type, title, comments, tags, id }) => {
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const lib = socket.librarian();
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const resp = await lib.loadDocument(
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document,
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mime_type,
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title,
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comments ?? "",
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tags ?? [],
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id,
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);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp, null, 2) }] };
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},
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);
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server.tool(
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"remove_document",
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"Remove a document from the library",
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{
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id: z.string().describe("Document ID to remove"),
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collection: z.string().optional().describe("Collection name"),
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},
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async ({ id, collection }) => {
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const lib = socket.librarian();
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const resp = await lib.removeDocument(id, collection);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp) }] };
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},
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);
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// ===================== Prompt tools =====================
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server.tool(
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"get_prompts",
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"List available prompt templates",
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{},
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async () => {
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const cfg = socket.config();
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const prompts = await cfg.getPrompts();
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return { content: [{ type: "text" as const, text: JSON.stringify(prompts, null, 2) }] };
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},
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);
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server.tool(
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"get_prompt",
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"Get a specific prompt template",
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{
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id: z.string().describe("Prompt template ID"),
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},
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async ({ id }) => {
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const cfg = socket.config();
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const prompt = await cfg.getPrompt(id);
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return { content: [{ type: "text" as const, text: JSON.stringify(prompt, null, 2) }] };
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},
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);
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// ===================== Knowledge core tools =====================
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server.tool(
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"get_knowledge_cores",
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"List available knowledge graph cores",
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{},
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async () => {
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const knowledge = socket.knowledge();
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const cores = await knowledge.getKnowledgeCores();
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return { content: [{ type: "text" as const, text: JSON.stringify(cores, null, 2) }] };
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},
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);
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server.tool(
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"delete_kg_core",
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"Delete a knowledge graph core",
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{
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id: z.string().describe("Knowledge core ID"),
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collection: z.string().optional().describe("Collection name"),
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},
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async ({ id, collection }) => {
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const knowledge = socket.knowledge();
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const resp = await knowledge.deleteKgCore(id, collection);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp) }] };
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},
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);
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server.tool(
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"load_kg_core",
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"Load a knowledge graph core",
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{
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id: z.string().describe("Knowledge core ID"),
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flow: z.string().describe("Flow to use for loading"),
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collection: z.string().optional().describe("Collection name"),
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},
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async ({ id, flow, collection }) => {
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const knowledge = socket.knowledge();
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const resp = await knowledge.loadKgCore(id, flow, collection);
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return { content: [{ type: "text" as const, text: JSON.stringify(resp) }] };
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},
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);
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|
|
@ -160,6 +416,7 @@ export function createMcpServer(config: {
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export async function run(): Promise<void> {
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const { server, socket } = createMcpServer({
|
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gatewayUrl: process.env.GATEWAY_URL ?? "ws://localhost:8088/api/v1/socket",
|
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user: process.env.USER_ID ?? "mcp",
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token: process.env.GATEWAY_SECRET,
|
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flowId: process.env.FLOW_ID ?? "default",
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});
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|
|
@ -167,8 +424,8 @@ export async function run(): Promise<void> {
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const transport = new StdioServerTransport();
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await server.connect(transport);
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process.on("SIGINT", async () => {
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await socket.close();
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process.on("SIGINT", () => {
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socket.close();
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process.exit(0);
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});
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}
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|
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