Add the full MCP tool pipeline enabling agents to invoke external tools
(like Brave Search) via MCP servers:
- Add ToolRequest/ToolResponse types and mcp-tool topics to @trustgraph/base
- Create McpToolService (FlowProcessor) that connects to external MCP servers
via @modelcontextprotocol/sdk StreamableHTTP transport
- Add createMcpTool() to wire MCP tools into the agent's ReAct loop
- Implement config-driven tool registration in AgentService with backward-
compatible fallback to hardcoded tools
- Add tool filtering by group and state (port of Python tool_filter.py)
- Register mcp-tool in gateway dispatcher and export from @trustgraph/flow
- Fix flow restart race condition: skip restart when flow definitions unchanged
- Update seed config with MCP server config and tool definitions
- Add run scripts for MCP tool service and Brave Search MCP server
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Wire up the query and retrieval side of the pipeline so the agent can
answer questions from stored knowledge:
- Triples query service (FalkorDB) — all SPO pattern queries via NATS
- Graph embeddings query service (Qdrant) — entity vector similarity
- Document embeddings query service (Qdrant) — chunk vector similarity
- Graph RAG service — full concept→entity→traverse→score→synthesize pipeline
- Document RAG service — embed→find chunks→synthesize pipeline
- Runner scripts for chunker, extractor, embeddings (missing from Phase 5)
- Add DocumentEmbeddingsRequest/Response schema types
- Add RAG prompt templates (extract-concepts, edge-scoring, synthesize)
- Add graph/doc embeddings query topics to seed config + flow manager
- Add all pipeline/query/retrieval services to docker-compose
- 8 new runner scripts, 8 new pnpm script aliases
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Add end-to-end document processing pipeline:
- PDF decoder service (pdfjs-dist) extracts text per page from librarian docs
- Ollama native LLM service for local model inference
- FalkorDB triples store FlowProcessor consumer
- Qdrant graph embeddings store FlowProcessor consumer
- Fix spec name collisions in chunker/extractor (input→chunk-input, etc.)
- Gateway /load endpoint to trigger document processing
- Align flow manager blueprint and seed config with full pipeline topics
- Add runner scripts and test coverage for document load
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Flow Management Service:
- FlowManagerService (AsyncProcessor) handling list/get/start/stop flows
and list/get blueprints via kebab-case wire format
- Default blueprint with all service topic mappings
- Pushes flow config to config service on start/stop
Config Seeding:
- seed-config.ts script pushes prompt templates (extract-relationships,
extract-definitions, document-prompt, kg-prompt) and default flow
definition via gateway REST API
Integration Tests:
- Librarian CRUD: add-document, list-documents, get-content, delete
- Agent query: verifies routing through gateway to agent service
- Skip flags: SKIP_LIBRARIAN=1, SKIP_AGENT=1
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
