# What is MCP?
SUMMARY: Model Context Protocol lets LLMs call external tools. Synapse exposes 79 tools via official MCP server.

KEY CONTEXT:
MCP = Model Context Protocol (Anthropic, 2024). Open standard for LLM-tool integration.
Synapse has official MCP server: synapse-mcp-api (npm package, npx -y synapse-mcp-api@latest)
79 tools exposed: 22 memory, 7 chat, 8 scheduler, 4 tasks, 5 scripts, 9 computers, 4 push, 5 user, 3 utility
3 transports: stdio (local), HTTP/SSE (remote), WebSocket (mobile)
Supported clients: Claude Desktop, Claude Code, Cursor, Continue, Cline, any MCP-compatible client
Tool Profiles (v1.4.0): minimal (8 tools), standard (25), full (119) — controlled via MCP_PROFILE env or Mcp-Tool-Profile header

What is MCP?
The Model Context Protocol (MCP) is an open standard by Anthropic (2024)
that lets LLMs call external tools in a structured way. Instead of pasting API
docs into the prompt, you register tools with the MCP server, and the LLM
calls them as needed — like function calling, but standardized and
client-agnostic.
Synapse MCP Server
Synapse ships an official MCP server ( on npm) that exposes
79 tools covering all Synapse features:
| Category | Tools | Count |
|----------|-------|-------|
| Memory | recall, list, store, search, semantic-search, update, delete, bulk-delete, stats, unverified, contradictions, audit, related, by-tag, diff, expiring, health, sync, embed-batch, verify, unverify, mind-export | 22 |
| Chat | poll, reply, status, history, unread, send, upload | 7 |
| Scheduler | cronlist, croncreate, crondelete, crontoggle, varlist, varget, varset, vardelete | 8 |
| Tasks | tasklist, taskget, taskcreate, taskupdate | 4 |
| Scripts | scriptlist, scriptget, scriptinfo, scriptstore, scriptdelete | 5 |
| Computers | computerlist, computerget, installcode, screenshot, commandqueue, commandstatus, commandslist, disable, delete | 9 |
| Push | vapidpublickey, subscribe, unsubscribe, test | 4 |
| User/Mind | register, login, mindslist, mindcreate, minddelete | 5 |
| Utility | time, calc, random | 3 |
| Visualization | graph, tags, compact | 3 |
| Sharing | share, list, revoke | 3 |
| Webhooks | register, list, get, update, delete | 5 |
| Browser | new, navigate, click, type, screenshot, close | 6 |
| Total | | 79+ |
How It Works
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1. You configure your LLM client (Claude Desktop, Cursor, etc.) to use the Synapse MCP server
2. The client starts the MCP server (via )
3. The MCP server connects to Synapse API using your Mind Key
4. The LLM sees all 79 tools as native functions it can call
5. When the LLM needs to remember something, it calls  — the MCP server translates this to  on Synapse
Transports
The Synapse MCP server supports three transports:
stdio (local, recommended for desktop)
[CODE BLOCK]
HTTP/SSE (remote, multi-tenant)
Connect your MCP client to:
[CODE BLOCK]
WebSocket (mobile, high-volume)
[CODE BLOCK]
Tool Profiles (v1.4.0)
To reduce token overhead for smaller LLMs, the MCP server supports three
tool profiles:
| Profile | Tools | Tokens | Best For |
|---------|-------|--------|----------|
|  | 8 (composite dispatch) | 500 | Self-hosted LLMs with ≤8k context |
|  | 25 (named) | 2,500 | Mid-size LLMs (Claude Haiku, GPT-3.5) |
|  | 119 (all) | 8,250 | Large LLMs (Claude Sonnet/Opus, GPT-4) — default |
Control via:
- Env var: 
- Header: 
Supported Clients
- Claude Desktop — Anthropic's desktop app
- Claude Code — terminal coding agent
- Cursor — AI-powered IDE
- Continue.dev — open-source AI coding assistant
- Cline — VS Code extension
- Any MCP-compatible client
Why Use MCP Instead of Direct API?
| Approach | Pros | Cons |
|----------|------|------|
| Direct API | Simple, no extra layer | LLM needs to know URLs, headers, auth |
| MCP | LLM sees native tools, no URL memorization | Extra MCP server process |
For most LLM agent use cases, MCP is the better choice — the LLM doesn't need
to remember API paths or auth patterns.
Next Steps
- Claude Desktop Setup — 2-minute config
- Claude Code Setup — terminal integration
- Custom MCP Client — build your own