Team Relay MCP

Đọc, tìm kiếm và ghi chú trong kho Obsidian thông qua máy chủ cộng tác Team Relay. Hỗ trợ thư mục chia sẻ và đồng bộ thời gian thực.

Tài liệu

EVC Team Relay - MCP Server

PyPI Docker Hub License: MIT MCP Install via Spark

Give your AI agent read/write access to your Obsidian vault.

Your agent reads your notes, creates new ones, and stays in sync — all through the Team Relay API.

Works with Claude Code, Codex CLI, OpenCode, and any MCP-compatible client.

evc-team-relay-mcp MCP server

Quick Start

1. Install

Option A — from PyPI (recommended):

No installation needed — uvx downloads and runs automatically. Skip to step 2.

Option B — from source:

git clone https://github.com/entire-vc/evc-team-relay-mcp.git
cd evc-team-relay-mcp
uv sync   # or: pip install .

2. Configure your AI tool

Add the MCP server to your tool's config. Choose one authentication method:

Agent key (recommended) — create a key in the Obsidian plugin → Team Relay settings → Agent Keys. Supports read and write: list_files, read_file, tr_search, and upsert_file all work with a single key. Quickstart →

Email + password — use a dedicated agent account on your Relay instance.

Claude Code — agent key

Add to .mcp.json in your project root or ~/.claude/.mcp.json:

{
  "mcpServers": {
    "evc-relay": {
      "command": "uvx",
      "args": ["evc-team-relay-mcp"],
      "env": {
        "RELAY_CP_URL": "https://cp.yourdomain.com",
        "RELAY_AGENT_KEY": "tr_agent_your_key_here"
      }
    }
  }
}
Claude Code — email/password
{
  "mcpServers": {
    "evc-relay": {
      "command": "uvx",
      "args": ["evc-team-relay-mcp"],
      "env": {
        "RELAY_CP_URL": "https://cp.yourdomain.com",
        "RELAY_EMAIL": "agent@yourdomain.com",
        "RELAY_PASSWORD": "your-password"
      }
    }
  }
}
Codex CLI

Add to your codex.json:

{
  "mcp_servers": {
    "evc-relay": {
      "type": "stdio",
      "command": "uvx",
      "args": ["evc-team-relay-mcp"],
      "env": {
        "RELAY_CP_URL": "https://cp.yourdomain.com",
        "RELAY_AGENT_KEY": "tr_agent_your_key_here"
      }
    }
  }
}
OpenCode

Add to opencode.json:

{
  "mcpServers": {
    "evc-relay": {
      "command": "uvx",
      "args": ["evc-team-relay-mcp"],
      "env": {
        "RELAY_CP_URL": "https://cp.yourdomain.com",
        "RELAY_AGENT_KEY": "tr_agent_your_key_here"
      }
    }
  }
}
From source (all tools)

If you installed from source instead of PyPI, replace "command": "uvx" / "args": ["evc-team-relay-mcp"] with:

"command": "uv",
"args": ["run", "--directory", "/path/to/evc-team-relay-mcp", "relay_mcp.py"]

Environment variables:

VariableRequiredDescription
RELAY_CP_URLYesControl plane base URL
RELAY_AGENT_KEYOne ofAgent key from plugin settings — read + write (recommended)
RELAY_EMAILOne ofAccount email (email/password mode)
RELAY_PASSWORDOne ofAccount password (email/password mode)

Ready-to-copy config templates are also in config/.

3. Use it

Your AI agent now has these tools:

ToolDescription
authenticateAuthenticate with credentials (auto-managed)
list_sharesList accessible shares (filter by kind, ownership)
list_filesList files in a folder share
read_fileRead a file by path from a folder share
read_documentRead document by doc_id (low-level)
upsert_fileCreate or update a file by path
write_documentWrite to a document by doc_id
delete_fileDelete a file from a folder share

Typical workflow: list_shares -> list_files -> read_file / upsert_file

Authentication is automatic — the server logs in and refreshes tokens internally.


Remote Deployment (HTTP Transport)

For shared or server-side deployments, run as an HTTP server:

# Direct
uv run relay_mcp.py --transport http --port 8888

# Docker (pulls from Docker Hub automatically)
RELAY_CP_URL=https://cp.yourdomain.com \
RELAY_EMAIL=agent@yourdomain.com \
RELAY_PASSWORD=your-password \
docker compose up -d

# Or pull explicitly
docker pull deadalusevc/evc-team-relay-mcp:latest

By default the server binds to 127.0.0.1 (localhost-only) — the endpoint is not reachable over the network even if the host has a public IP. This matches the common case of a single MCP client on the same machine as the server.

Then configure your MCP client to connect via HTTP:

{
  "mcpServers": {
    "evc-relay": {
      "type": "streamable-http",
      "url": "http://127.0.0.1:8888/mcp"
    }
  }
}

Remote access via SSH tunnel (recommended)

If your MCP client runs on a different machine than the server, tunnel to the localhost-bound port instead of exposing it publicly:

# From the client machine, forward local 8888 to the server's localhost:8888
ssh -N -L 8888:127.0.0.1:8888 user@your-server

Then point the client config at http://127.0.0.1:8888/mcp as above — traffic goes through the SSH tunnel, and the server's bind address never needs to change.

Public / reverse-proxy binding (opt-in)

If you genuinely need the server to accept connections from other hosts directly (e.g. it sits behind a reverse proxy that terminates TLS and handles auth), pass --host explicitly:

uv run relay_mcp.py --transport http --port 8888 --host 0.0.0.0

Only do this behind a reverse proxy or firewall — the MCP HTTP endpoint itself has no built-in authentication, so binding it to 0.0.0.0 on an open network exposes every relay tool call to anyone who can reach the port.


Security

The MCP server provides significant security advantages over shell-based integrations:

  • No shell execution — all operations are Python function calls via JSON-RPC, eliminating command injection risks
  • No CLI arguments — credentials and tokens are never passed as process arguments (invisible in ps output)
  • Automatic token management — the server handles login, JWT refresh, and token lifecycle internally; the agent never touches raw tokens
  • Typed inputs — all parameters are validated against JSON Schema before execution
  • Single persistent process — no per-call shell spawning, no environment leakage between invocations

Note: If you're using the OpenClaw skill (bash scripts), consider migrating to this MCP server for a more secure and maintainable integration.


How It Works

┌─────────────┐      MCP        ┌──────────────┐     REST API     ┌──────────────┐     Yjs CRDT      ┌──────────────┐
│  AI Agent   │ ◄────────────► │  MCP Server  │ ◄─────────────► │  Team Relay  │ ◄──────────────► │   Obsidian   │
│ (any tool)  │  stdio / HTTP  │ (this repo)  │    read/write   │   Server     │    real-time     │    Client    │
└─────────────┘                └──────────────┘                 └──────────────┘      sync         └──────────────┘

The MCP server wraps Team Relay's REST API into standard MCP tools. Team Relay stores documents as Yjs CRDTs and syncs them to Obsidian clients in real-time. Changes made by the agent appear in Obsidian instantly — and vice versa.


Prerequisites

  • Python 3.10+ with uv (recommended) or pip
  • A running EVC Team Relay instance (self-hosted or hosted)
  • A user account on the Relay control plane

Part of the Entire VC Toolbox

ProductWhat it doesLink
Team RelaySelf-hosted collaboration serverrepo
Team Relay PluginObsidian plugin for Team Relayrepo
Relay MCPMCP server for AI agentsthis repo
OpenClaw SkillOpenClaw agent skill (bash)repo
Local SyncVault <-> AI dev tools syncrepo
Spark MCPMCP server for AI workflow catalogrepo

Community

License

MIT