ktx/packages/context/src/scan/entity-details.ts
Andrey Avtomonov b759a4a286
feat(mcp):added MCP server (#97)
* docs(specs): design research-agent MCP tools and ktx mcp daemon

Adds the 2026-05-14 design spec for exposing four new MCP tools
(discover_data, entity_details, dictionary_search, sql_execution),
shipping a ktx-research skill, and introducing an HTTP-only ktx mcp
daemon so external agents can use KTX as a research-capable context
layer.

* Refine research-agent MCP tools spec after adversarial review iteration 1

* Refine research-agent MCP tools spec after adversarial review iteration 2

* Refine research-agent MCP tools spec after adversarial review iteration 3

* Refine spec: drop connectionName compat carve-out and ground summary/snippet provenance per kind

* feat(daemon): validate read-only SQL with sqlglot

* feat(context): expose read-only SQL validation port

* feat(context): register MCP sql execution tool

* feat(context): execute MCP SQL through validated connector path

* test(context): update SQL analysis port fixtures

* docs: add research-agent MCP sql execution foundation plan

* feat(context): add scan-backed entity details service

* feat(context): register MCP entity details tool

* feat(context): expose local MCP entity details

* test(context): align entity details scan fixtures

* docs: add research-agent MCP entity_details plan

* feat(context): add dictionary search service

* feat(context): register MCP dictionary search tool

* feat(context): expose local MCP dictionary search

* docs: add research-agent MCP dictionary_search plan

* feat: add MCP discover data service

* feat: expose discover data MCP tool

* feat: wire local discover data MCP port

* docs: add research-agent MCP discover_data plan

* feat(cli): add mcp http security helpers

* feat(cli): host mcp over streamable http

* feat(cli): manage mcp daemon lifecycle

* feat(cli): add ktx mcp commands

* fix(cli): stabilize mcp daemon verification

* docs: add research-agent MCP http daemon plan

* feat(cli): install KTX research skill

* feat(cli): configure MCP clients in setup agents

* feat(cli): support Claude local MCP setup scope

* docs: add research-agent MCP setup-agents plan

* refactor(context): use connectionId in warehouse verification tools

* docs(context): update ingest verification prompts for connectionId

* docs: add research-agent MCP ingest contract convergence plan

* chore: build runtime artifacts in conductor setup

---------

Co-authored-by: Andrey Avtomonov <7889985+andreybavt@users.noreply.github.com>
2026-05-15 02:35:09 +02:00

315 lines
9.7 KiB
TypeScript

import type { KtxLocalProject } from '../project/index.js';
import { readLocalScanStructuralSnapshot } from './local-structural-artifacts.js';
import type {
KtxConnectionDriver,
KtxScanReport,
KtxSchemaColumn,
KtxSchemaSnapshot,
KtxSchemaTable,
KtxTableRef,
} from './types.js';
export type KtxEntityDetailsTableInput = string | KtxTableRef;
export interface KtxEntityDetailsInput {
connectionId: string;
entities: Array<{
table: KtxEntityDetailsTableInput;
columns?: string[];
}>;
}
export interface KtxEntityDetailsSnapshotInfo {
syncId: string;
extractedAt: string;
scanRunId: string | null;
}
export interface KtxEntityDetailsColumn {
name: string;
nativeType: string;
normalizedType: string;
dimensionType: KtxSchemaColumn['dimensionType'];
nullable: boolean;
primaryKey: boolean;
comment: string | null;
}
export interface KtxEntityDetailsRecord {
ok: true;
connectionId: string;
tableRef: KtxTableRef;
display: string;
kind: KtxSchemaTable['kind'];
comment: string | null;
estimatedRows: number | null;
columns: KtxEntityDetailsColumn[];
foreignKeys: KtxSchemaTable['foreignKeys'];
snapshot: KtxEntityDetailsSnapshotInfo;
}
export type KtxEntityDetailsErrorCode = 'scan_missing' | 'table_not_found' | 'ambiguous_table' | 'column_not_found';
export interface KtxEntityDetailsErrorResult {
ok: false;
connectionId: string;
table: KtxEntityDetailsTableInput;
snapshot?: KtxEntityDetailsSnapshotInfo;
error: {
code: KtxEntityDetailsErrorCode;
message: string;
candidates?: Array<{ tableRef: KtxTableRef; display: string }> | string[];
};
}
export interface KtxEntityDetailsResponse {
results: Array<KtxEntityDetailsRecord | KtxEntityDetailsErrorResult>;
}
interface LatestScan {
report: KtxScanReport;
snapshot: KtxSchemaSnapshot;
}
interface ResolveResult {
table: KtxSchemaTable | null;
error?: Omit<KtxEntityDetailsErrorResult['error'], 'message'> & { message: string };
}
function normalize(value: string | null | undefined): string {
return (value ?? '').toLowerCase();
}
function refsEqual(left: KtxTableRef, right: KtxTableRef): boolean {
return (
normalize(left.catalog) === normalize(right.catalog) &&
normalize(left.db) === normalize(right.db) &&
normalize(left.name) === normalize(right.name)
);
}
function cleanIdentifierPart(part: string): string {
return part.trim().replace(/^["'`\[]|["'`\]]$/g, '');
}
function splitDisplay(display: string): string[] {
return display
.trim()
.split('.')
.map(cleanIdentifierPart)
.filter(Boolean);
}
function displayForTable(driver: KtxConnectionDriver, table: KtxTableRef): string {
if (driver === 'sqlite') {
return table.name;
}
return [table.catalog, table.db, table.name].filter((part): part is string => Boolean(part)).join('.');
}
function tableRef(table: KtxSchemaTable): KtxTableRef {
return { catalog: table.catalog, db: table.db, name: table.name };
}
function candidateList(
driver: KtxConnectionDriver,
tables: KtxSchemaTable[],
): Array<{ tableRef: KtxTableRef; display: string }> {
return tables
.map((table) => ({
tableRef: tableRef(table),
display: displayForTable(driver, table),
}))
.sort((left, right) => left.display.localeCompare(right.display));
}
function parseDisplayRef(driver: KtxConnectionDriver, display: string): KtxTableRef | null {
const parts = splitDisplay(display);
if (driver === 'sqlite') {
return parts.length === 1 ? { catalog: null, db: null, name: parts[0]! } : null;
}
if (driver === 'bigquery' || driver === 'snowflake' || driver === 'sqlserver') {
return parts.length === 3 ? { catalog: parts[0]!, db: parts[1]!, name: parts[2]! } : null;
}
if (parts.length === 2) {
return { catalog: null, db: parts[0]!, name: parts[1]! };
}
if (parts.length === 3) {
return { catalog: parts[0]!, db: parts[1]!, name: parts[2]! };
}
return null;
}
function resolveTable(snapshot: KtxSchemaSnapshot, input: KtxEntityDetailsTableInput): ResolveResult {
if (typeof input !== 'string') {
const table = snapshot.tables.find((candidate) => refsEqual(candidate, input)) ?? null;
return table
? { table }
: {
table: null,
error: {
code: 'table_not_found',
message: `Table not found in latest scan: ${displayForTable(snapshot.driver, input)}`,
candidates: candidateList(snapshot.driver, snapshot.tables),
},
};
}
const parsed = parseDisplayRef(snapshot.driver, input);
if (parsed) {
const table = snapshot.tables.find((candidate) => refsEqual(candidate, parsed)) ?? null;
return table
? { table }
: {
table: null,
error: {
code: 'table_not_found',
message: `Table not found in latest scan: ${input}`,
candidates: candidateList(snapshot.driver, snapshot.tables),
},
};
}
const byName = snapshot.tables.filter((candidate) => normalize(candidate.name) === normalize(input));
if (byName.length === 1) {
return { table: byName[0]! };
}
if (byName.length > 1) {
return {
table: null,
error: {
code: 'ambiguous_table',
message: `Table name "${input}" is ambiguous across schemas/catalogs; pass a structured table ref.`,
candidates: candidateList(snapshot.driver, byName),
},
};
}
return {
table: null,
error: {
code: 'table_not_found',
message: `Table not found in latest scan: ${input}`,
candidates: candidateList(snapshot.driver, snapshot.tables),
},
};
}
function toColumn(column: KtxSchemaColumn): KtxEntityDetailsColumn {
return {
name: column.name,
nativeType: column.nativeType,
normalizedType: column.normalizedType,
dimensionType: column.dimensionType,
nullable: column.nullable,
primaryKey: column.primaryKey,
comment: column.comment,
};
}
function snapshotInfo(report: KtxScanReport, snapshot: KtxSchemaSnapshot): KtxEntityDetailsSnapshotInfo {
return {
syncId: report.syncId,
extractedAt: snapshot.extractedAt,
scanRunId: report.runId ?? null,
};
}
async function readJson<T>(project: KtxLocalProject, path: string): Promise<T> {
return JSON.parse((await project.fileStore.readFile(path)).content) as T;
}
async function latestScan(project: KtxLocalProject, connectionId: string): Promise<LatestScan | null> {
const root = `raw-sources/${connectionId}/live-database`;
let listed;
try {
listed = await project.fileStore.listFiles(root);
} catch {
return null;
}
const reportPath = listed.files.filter((path) => path.endsWith('/scan-report.json')).sort().at(-1);
if (!reportPath) {
return null;
}
const report = await readJson<KtxScanReport>(project, reportPath);
const rawSourcesDir = report.artifactPaths.rawSourcesDir ?? reportPath.slice(0, -'/scan-report.json'.length);
const snapshot = await readLocalScanStructuralSnapshot({
project,
connectionId,
driver: report.driver,
rawSourcesDir,
extractedAtFallback: report.createdAt,
});
return { report, snapshot };
}
export function createKtxEntityDetailsService(project: KtxLocalProject) {
return {
async read(input: KtxEntityDetailsInput): Promise<KtxEntityDetailsResponse> {
const scan = await latestScan(project, input.connectionId);
if (!scan) {
return {
results: input.entities.map((entity) => ({
ok: false,
connectionId: input.connectionId,
table: entity.table,
error: {
code: 'scan_missing',
message: `No live-database scan found for connection "${input.connectionId}"; run \`ktx ingest ${input.connectionId}\` or \`ktx scan ${input.connectionId}\`.`,
},
})),
};
}
const info = snapshotInfo(scan.report, scan.snapshot);
const results: KtxEntityDetailsResponse['results'] = [];
for (const entity of input.entities) {
const resolved = resolveTable(scan.snapshot, entity.table);
if (!resolved.table) {
results.push({
ok: false,
connectionId: input.connectionId,
table: entity.table,
snapshot: info,
error: resolved.error!,
});
continue;
}
const requested = new Set((entity.columns ?? []).map((column) => normalize(column)));
const columns = requested.size
? resolved.table.columns.filter((column) => requested.has(normalize(column.name)))
: resolved.table.columns;
if (requested.size && columns.length !== requested.size) {
const found = new Set(columns.map((column) => normalize(column.name)));
const missing = [...requested].filter((column) => !found.has(column));
results.push({
ok: false,
connectionId: input.connectionId,
table: entity.table,
snapshot: info,
error: {
code: 'column_not_found',
message: `Column(s) not found on ${displayForTable(scan.snapshot.driver, resolved.table)}: ${missing.join(', ')}`,
candidates: resolved.table.columns.map((column) => column.name),
},
});
continue;
}
results.push({
ok: true,
connectionId: input.connectionId,
tableRef: tableRef(resolved.table),
display: displayForTable(scan.snapshot.driver, resolved.table),
kind: resolved.table.kind,
comment: resolved.table.comment,
estimatedRows: resolved.table.estimatedRows,
columns: columns.map(toColumn),
foreignKeys: resolved.table.foreignKeys,
snapshot: info,
});
}
return { results };
},
};
}