Community: mcp-server-deerflow-kinthai — Expose DeerFlow as a Standard MCP Server

[kinthaiofficial]

Hi DeerFlow community! 👋

We built mcp-server-deerflow-kinthai — a standalone Python package that exposes DeerFlow's deep capabilities via the standard Model Context Protocol, so any MCP client (OpenClaw, Claude Desktop, Cursor, etc.) can discover and invoke DeerFlow tools.

Tools exposed

Tool	Description
deep_research	Multi-source web research with cross-verification
data_analysis	Data analysis with DuckDB (CSV/Excel)
chart_visualization	26+ chart types (line, bar, pie, scatter, sankey, etc.)
ppt_generation	PowerPoint presentation generation
image_generation	AI image generation
consulting_analysis	Business analysis (SWOT, Porter's Five Forces, etc.)

Why?

DeerFlow is powerful but currently speaks its own API. MCP is the emerging interop standard that agent frameworks like Claude Desktop, Cursor, and our own OpenClaw already support natively. This wrapper lets users point any MCP-aware client at DeerFlow with zero code.

Get it

• Repo: https://github.com/kinthaiofficial/mcp-server-deerflow-kinthai
• License: MIT
• Status: v0.1.0 initial release

Feedback and contributions welcome! We'll follow DeerFlow releases and keep the wrapper compatible.

— Built by the KinthAI team.

[kinthaiofficial]

Note from the author — open to upstreaming 🤝

If the DeerFlow maintainers would prefer this MCP wrapper to live inside the bytedance/deer-flow repository itself (e.g. under a contrib/ or integrations/ folder), I'm happy to contribute it as a PR.

The package is small and self-contained:

• src/mcp_server_deerflow_kinthai/ — three Python files (server, main, init)
• tests/ — two test files
• pyproject.toml with MIT license

Either path works for us — standalone community package or upstream contribution. Whatever is best for DeerFlow users. Happy to adjust namespace, packaging, or integration approach based on maintainer preferences.

Just leave a comment or ping me here and I'll open a PR.