mcp-glm-kimi-ollama
Provides tools for interacting with a local Ollama instance, enabling private, offline, zero-cost inference with models such as qwen3:8b.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-glm-kimi-ollamaanalyze this image and describe what you see"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-glm-kimi-ollama
Free & low-cost LLM access for Claude Code — three MCP servers covering GLM (Zhipu), Kimi (Moonshot) and local Ollama models.
🆓 GLM — permanently-free
glm-4-flashvia the Zhipu China endpoint🎁 Kimi — Moonshot
kimi-k2.6(new accounts get a ¥15 credit)🖥️ Ollama — fully local, private, zero-cost models (e.g.
qwen3:8b)
All three run over stdio via Node.js — no Python or uv required (Windows users often find python is just a Store stub).
Why
Claude Code is powerful, but API costs add up. This project gives you three cheaper/offline "delegates" you can call from Claude Code:
Provider | Model | Cost | Best for |
GLM (Zhipu) |
| free forever | daily Q&A, translation, code gen |
Kimi (Moonshot) |
| ¥15 credit on signup | vision ( |
Ollama (local) |
| free, offline | privacy, batch, mechanical tasks |
Related MCP server: openai-mcp
Quick start
1. Kimi MCP (patched for the China endpoint)
claude mcp add kimi -s user \
-e MOONSHOT_API_KEY=sk-xxx \
-- npx -y mcp-glm-kimi-ollama mcp-kimi⚠️ Why the patch matters: the upstream
kimi-api-mcphardcodes the international endpointapi.moonshot.aiand a retired modelmoonshot-v1-128k. China-registered keys return 401 against the wrong host, and the old model no longer exists on the CN endpoint. This repo patches both (seesrc/kimi-server.mjs), defaulting toapi.moonshot.cn+kimi-k2.6.
2. GLM MCP (free)
claude mcp add glm -s user \
-e GLM_API_KEY=xxx.yyy \
-e GLM_BASE_URL=https://open.bigmodel.cn/api/anthropic \
-e GLM_OFFPEAK_MODEL=glm-4-flash \
-e GLM_PEAK_MODEL=glm-4-flash \
-e GLM_CHEAP_MODEL=glm-4-flash \
-e GLM_DELEGATE=on \
-- npx -y glm-mcp3. Ollama MCP (local, optional)
winget install Ollama.Ollama
ollama pull qwen3:8b
claude mcp add ollama -s user -e ASK_OLLAMA_MODEL=qwen3:8b -- npx -y @ask-llm/ollama-mcpDevelopment
npm install
npm testDocs
docs/glm-mcp.md — GLM configuration details & troubleshooting
docs/kimi-mcp.md — Kimi patch rationale, endpoints & models
docs/ollama.md — local Ollama setup, incl. mirror download tips for mainland China
License
MIT
Maintenance
Resources
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