Personal MCP Assistant
Embeddings can be generated through an OpenAI-compatible embeddings endpoint configured via EMBEDDING_URL (1536 dimensions), used to index notes and ingested visual documents for hybrid RAG retrieval.
Backs the assistant's memory: notes, calendar events, agent facts and embeddings are stored in PostgreSQL with the pgvector extension, powering the hybrid retrieval (vector similarity + full-text tsvector combined with reciprocal rank fusion) used by the search and cross-context summary tools. Schema is applied from scripts/init_db.sql.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Personal MCP AssistantSchedule Sprint review next Monday 3-4pm IST and summarize prep from my notes."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Personal MCP Assistant
Designed & developed by NIKHIL CHARY SRIRAMOJU · GitHub · LinkedIn
Groq-powered ReAct agent over your calendar, notes and scanned images, exposed through the Model Context Protocol. Hybrid RAG (pgvector + tsvector + RRF), CNN/OCR vision worker, Next.js UI with a 3D context graph, all in Docker Compose.
Two ways to run
Static site (GitHub Pages):
docs/— no build, runs fully in the browser (Groq BYOK, local hybrid RAG, in-browser CNN/OCR, Three.js graph). SeeGITHUB_PAGES_GUIDE.md.Full stack (Docker): TypeScript MCP server + Postgres/pgvector + Python CNN worker, below.
Related MCP server: SoloOS MCP Server
Run it
cp .env.example .env # set GROQ_API_KEY
docker compose up --buildUI: http://localhost:3000 · API: http://localhost:4000 · MCP: http://localhost:4000/mcp
The schema is applied automatically on first Postgres start from
scripts/init_db.sql. Re-apply manually:docker compose exec -T postgres psql -U mcp -d mcp < scripts/init_db.sql
Test it
# health
curl localhost:4000/health
# add a note via the agent
curl -s localhost:4000/api/chat -H 'content-type: application/json' \
-d '{"sessionId":"t1","message":"Create a note titled Sprint plan: finish API auth, review CNN worker. Tag it work."}'
# add an event, then ask for a prep summary
curl -s localhost:4000/api/chat -H 'content-type: application/json' \
-d '{"sessionId":"t1","message":"Schedule Sprint review next Monday 3pm-4pm IST, then summarise prep from my notes."}'
# upload a whiteboard photo
curl -F file=@whiteboard.jpg localhost:4000/api/uploadCLI (no UI): npm i && DATABASE_URL=postgresql://mcp:mcp@localhost:5432/mcp GROQ_API_KEY=... CNN_WORKER_URL=http://localhost:8000 npm run cli
(run docker compose up postgres cnn-worker for the dependencies).
MCP Inspector / Claude Desktop: npx @modelcontextprotocol/inspector → Streamable HTTP → http://localhost:4000/mcp, or stdio via npm run mcp:stdio.
Layout
src/mcp tools (Zod) · src/agent Groq loop + reflection · src/rag embedder + RRF · src/cnn vision client · src/db pool · src/ui Next.js · docs/ static site · cnn-worker/ Python OCR/CNN · scripts/init_db.sql
Tools
get_events, create_event, reschedule_event, detect_schedule_conflicts, hybrid_search_notes, create_note, update_note, ingest_visual_document, store_agent_fact, retrieve_long_term_memory, reflect_and_validate, synthesize_cross_context_summary
Notes
llama-3.3-70b-versatileby default; changeGROQ_MODEL(e.g. a Llama 4 Scout id from Groq's model list).Groq has no embeddings endpoint, so embeddings are local-hashed by default or via
EMBEDDING_URL(1536 dims, OpenAI-compatible).First run: I couldn't run
npm install/Docker in my sandbox, so expect to fix a typing nit or two on first build. Send me the error and I'll patch it.
This server cannot be deployed
Maintenance
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Shared memory for teams that work with AI agents: meetings, email and calendar in one brain.
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