synapse mcp server

Basic MCP server that connects AI clients to your Synapse backend API.

tools exposed

• health_check

• search_memories

• list_recent_memories

• get_memory

• create_memory

• ask_synapse

Related MCP server: Neo4j Knowledge Graph MCP Server

setup

1. Install dependencies

cd /home/pranav/work/synapse/mcp
pip install -r requirements.txt

2. Configure environment

cp .env.example .env

Set values in .env:

• SYNAPSE_API_URL: backend URL, example http://localhost:8000

• SYNAPSE_API_TOKEN: user JWT token from Synapse login

• SYNAPSE_API_TIMEOUT: optional, default 15 seconds

3. Run server

python server.py

basic manual verification

After attaching this MCP server in your client (Claude/Cursor/VS Code), call tools in this order:

1. health_check

• Expected: backend ok and token_configured true.

2. list_recent_memories with limit 3

• Expected: ok true and memory list in data.

3. search_memories with a known query

• Expected: ok true and search results in data.

4. create_memory

• Example inputs:

  • memory_type: text

  • title: MCP smoke memory

  • text_content: created from mcp

• Expected: ok true and created memory in data.

5. get_memory with the id returned from create_memory

• Expected: same memory details.

6. ask_synapse with a simple question

• Expected: ok true and reply payload in data.

You can also call ask_synapse with use_internet: true to let the backend add web context to the answer when needed.

If any tool returns ok false:

• Check SYNAPSE_API_URL

• Check SYNAPSE_API_TOKEN validity

• Check backend logs for endpoint errors

claude desktop config example

{
  "mcpServers": {
    "synapse": {
      "command": "python",
      "args": ["/home/pranav/work/synapse/mcp/server.py"]
    }
  }
}