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* feat(setup): add Claude Desktop target and MCP-first agent setup Adds `ktx mcp stdio` and a `claude-desktop` setup target that generates a local plugin ZIP wiring the analytics skill and a stdio MCP config. Replaces the CLI-only agent install mode with MCP+analytics (default) and an optional admin CLI skill, renames the research skill to analytics, and lets interactive setup pick project vs global scope when every target supports it. Extracts a shared MCP server factory used by both HTTP and stdio entrypoints. * Add MCP agent client setup support * Polish setup output formatting * Add MCP tool polish design spec Design for slimming the MCP-registered surface from 25 to 11 tools, introducing memory_ingest, applying the per-tool polish kit (annotations, outputSchema, .describe(), in-band error wrapping, union-drift fixes, type-narrowed jsonToolResult), emitting progress notifications on sql_execution + sl_query, and refining the ktx-analytics SKILL.md to match. * Refine MCP tool polish design spec after adversarial review iteration 1 * Refine MCP tool polish design spec after adversarial review iteration 2 * Refine MCP tool polish design spec after adversarial review iteration 3 * refactor(context): rename memory capture service to ingest * feat(mcp): slim research tool surface * refactor(mcp): remove admin ports from server factory * refactor(cli): rename text ingest memory port * docs: update analytics skill for memory ingest * chore: verify mcp surface rename * Add MCP tool polish v1 surface change plan * feat(context): polish mcp tool metadata * fix(context): enforce resolved semantic layer compute sources * feat(context): emit mcp query progress stages * fix(context): keep mcp progress event internal * Add MCP tool polish v1 metadata & progress plan * Fix CI snapshot and docs checks
63 lines
2.2 KiB
TypeScript
63 lines
2.2 KiB
TypeScript
import { createDefaultKtxMcpServer, createLocalProjectMcpContextPorts } from '@ktx/context/mcp';
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import { createLocalProjectMemoryIngest } from '@ktx/context/memory';
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import type { KtxLocalProject } from '@ktx/context/project';
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import type { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
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import type { KtxCliIo } from './cli-runtime.js';
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import { createKtxCliIngestQueryExecutor } from './ingest-query-executor.js';
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import { createKtxCliScanConnector } from './local-scan-connectors.js';
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import { createManagedPythonSemanticLayerComputePort } from './managed-python-command.js';
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import { createManagedDaemonSqlAnalysisPort } from './managed-python-http.js';
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function noopMcpIo(): KtxCliIo {
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return {
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stdout: { write() {} },
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stderr: { write() {} },
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};
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}
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export async function createKtxMcpServerFactory(input: {
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project: KtxLocalProject;
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projectDir: string;
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cliVersion: string;
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io?: KtxCliIo;
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}): Promise<() => McpServer> {
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const io = input.io ?? noopMcpIo();
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const queryExecutor = createKtxCliIngestQueryExecutor(input.project);
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const semanticLayerCompute = await createManagedPythonSemanticLayerComputePort({
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cliVersion: input.cliVersion,
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installPolicy: 'auto',
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io,
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});
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const sqlAnalysis = createManagedDaemonSqlAnalysisPort({
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cliVersion: input.cliVersion,
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projectDir: input.projectDir,
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installPolicy: 'auto',
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io,
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});
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const contextTools = createLocalProjectMcpContextPorts(input.project, {
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semanticLayerCompute,
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queryExecutor,
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sqlAnalysis,
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localScan: {
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createConnector: async (connectionId) => createKtxCliScanConnector(input.project, connectionId),
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},
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});
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let memoryIngest: ReturnType<typeof createLocalProjectMemoryIngest> | undefined;
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try {
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memoryIngest = createLocalProjectMemoryIngest(input.project, { semanticLayerCompute, queryExecutor });
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} catch (error) {
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input.io?.stderr.write(`KTX MCP memory_ingest disabled: ${error instanceof Error ? error.message : String(error)}\n`);
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}
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return () =>
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createDefaultKtxMcpServer({
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name: 'ktx',
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version: input.cliVersion,
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userContext: { userId: 'local' },
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contextTools: {
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...contextTools,
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...(memoryIngest ? { memoryIngest } : {}),
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},
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});
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}
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