| name | local-rag-mcp |
| description | Use when querying, ingesting, or maintaining a local RAG MCP corpus for semantic document retrieval with privacy controls. |
Local RAG MCP
When to use
Use when the task requires semantic search, document ingestion, or querying a local vector database for context retrieval, and an appropriate MCP server is available.
Requirements / Checks
- Verify if a local RAG MCP server is configured in the environment (e.g., via
apx mcp list).
- Do NOT attempt to install or spin up Docker containers for vector databases without explicit user permission.
Workflow
- Identify Need: Determine if a query requires semantic retrieval vs. standard grep/glob.
- Check Configuration: Verify the connection to the MCP RAG server.
- Inventory Corpus: Use status/list tools if available before ingesting anything.
- Ingest (if necessary): Use file ingestion for approved files and string ingestion for approved fetched/web/clipboard content with clear source metadata.
- Query: Preserve exact user terms, add disambiguating context, and keep result limits small first.
- Expand: If a hit lacks surrounding context, fetch neighboring chunks before drawing conclusions.
- Clean Up: Delete stale or incorrectly ingested sources when requested.
- Synthesize: Incorporate retrieved context with citations to source/file and chunk.
Tool Model To Preserve
query_documents: keyword + semantic query; lower score means stronger match.
ingest_file: absolute-path document ingestion.
ingest_data: string/HTML/Markdown ingestion with source + format metadata.
delete_file: remove ingested file/source.
list_files and status: corpus inventory and DB health.
read_chunk_neighbors: expand around a search hit.
Safety Constraints
- Do NOT ingest sensitive personal data, secrets, or
.env files into the local RAG store.
- Warn the user if the local RAG implementation relies on external API calls for embeddings (e.g., sending data to OpenAI).
- Do not ingest whole repos by default; start with approved docs or scoped folders.
- Do not rely on semantic hits without reading neighbors/source when precision matters.
Validation / Done Criteria
- Relevant context is successfully retrieved.
- Ingestion explicitly excludes sensitive paths.
- Query result synthesis distinguishes retrieved evidence from inference.
References
references/rag-tool-model.md