wecom-docs-mcp-server

An ergonomic stdio MCP facade over WeCom's official robot-doc MCP backend. It proxies all 25 backend tools verbatim and adds a transform layer that makes the raw output usable by LLM agents:

• Schema passthrough — the tool list is fetched from the backend at startup, so it auto-tracks official updates. Zero schema maintenance.

• Cell unwrap — smartsheet values[field] = [{"type":"text","text":...}] cells become plain scalars (in a _rows view).

• ms → ISO — 13-digit ms-epoch timestamps (create_time, update_time) convert to ISO 8601.

• Chinese error hints — errcode 851003 etc. get _error_summary + _error_hint so the agent learns the fix, not just the code.

Relationship to the backend: This server requires the official robot-doc MCP backend (an apikey from WeCom admin → 智能文档机器人 → API). It is a thin proxy + ergonomics layer, not a replacement.

Why this exists

The official robot-doc backend is an HTTP (StreamableHttp) MCP server. Two friction points: (1) many MCP clients and dev workflows prefer stdio; (2) its raw output is agent-hostile — nested cell format, ms-epoch strings, opaque error codes. This server bridges both:

Related MCP server: dingtalk-wiki-mcp

Requirements

• Python 3.9+

• A WeCom 智能文档机器人 (Smart Doc Bot) with its API key — available to enterprises (≥10 members) via WeCom admin → 应用管理 → 智能文档机器人 → API.

Install

pip install wecom-docs-mcp-server

Or clone + editable:

git clone https://github.com/Beltran12138/wecom-docs-mcp-server
cd wecom-docs-mcp-server
pip install -e .

Configuration

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "wecom-doc": {
      "command": "wecom-docs-mcp-server",
      "env": { "WECOM_MCP_APIKEY": "your_apikey_here" }
    }
  }
}

Tools

All 25 backend tools are exposed verbatim (fetched live at startup). By domain:

Permission model (empirically observed 2026-07): get_doc_content and smartsheet_get_* use independent permission scopes. A bot may read a smartsheet via smartsheet_get_records (errcode 0) yet get 851003 no authority from get_doc_content on the same doc. Route reads by doc type.

Transforms (the value-add)

Applied automatically on every tools/call response:

1. _rows on smartsheet_get_records — a flattened view where cells are unwrapped to scalars and top-level record fields (record_id, create_time, …) are preserved. The original records array is kept intact.

2. ms → ISO on all successful dict payloads — 13-digit ms-epoch strings → ISO 8601. Alphanumeric IDs (q979lj) are untouched.

3. _error_summary + _error_hint on any non-zero errcode — Chinese explanation + concrete fix.

Usage

Read a smartsheet end-to-end:

User: read https://doc.weixin.qq.com/smartsheet/s3_xxx?scode=yyy

Agent:
1. smartsheet_get_sheet(url=...)          → sheet_id (e.g. "q979lj")
2. smartsheet_get_fields(sheet_id, url)   → field schema (types, IDs)
3. smartsheet_get_records(sheet_id, url)  → records + _rows (cells unwrapped, timestamps ISO)

Pass the full url (with ?scode=) rather than guessing docid — the backend resolves it. Manually extracting docid by stripping prefixes is error-prone (empirically: 301085 invalid docid).

Troubleshooting

Related

Tests

pip install -e ".[dev]"  # or: pip install pytest httpx
pytest

25 unit tests cover SSE/JSON parsing, ms-timestamp normalization, cell unwrap, error humanizing, and server routing/post-processing — all offline (httpx mocked).

License

MIT