# learning-mcp

HTTP MCP server exposing the pgvector learnings DB. Replaces direct `psql`/`ssh` access used by `rag-query`, `learn-seed`, `learn-inject`, `learn-context`.

- Transport: streamable HTTP (`/mcp`)
- Port: `9221`
- Backend: `learnings_embeddings` on the infra postgres container
- Embeddings: LiteLLM `/v1/embeddings` (`text-embedding-3-small`, 1536 dims)

## Tools

| Tool | Replaces |
|---|---|
| `learning_query` | `rag-query` |
| `learning_search_fts` | `pg_search_fts` in `pglearn.sh` |
| `learning_inject` | `learn-inject` |
| `learning_context` | `learn-context` |
| `learning_add` | `pg_insert_learning` |
| `learning_mark_applied` | `pg_mark_applied` |

## Env

```
PGHOST=postgres        # docker service name on infra
PGPORT=5432
PGUSER=agiliton
PGPASSWORD=...         # from vault ag.postgres.agiliton_password
PGDATABASE=agiliton
LITELLM_URL=https://llm.agiliton.cloud
LITELLM_API_KEY=...    # vault litellm.ai_coder_key or similar
EMBEDDING_MODEL=text-embedding-3-small
SENTRY_DSN=            # optional
```

## Local dev

```
npm install
LITELLM_API_KEY=$(vault get litellm.ai_coder_key) \
PGHOST=localhost PGPORT=5433 \
node src/http-server.js

curl -s http://127.0.0.1:9221/health
```

## Deploy

Built as `gitea.agiliton.internal:3000/christian/learning-mcp:latest` and attached to the infra docker-compose stack with the postgres network. Registered in `/opt/apps/litellm/config.yaml` as a streamable-HTTP MCP server (CF-3081 pattern).