Integrate Ollama's local LLM models for secure, on-premise AI and data control with MCP-compatible apps. Deploy custom m
by Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Slack
MCP server for Slack — enables Claude to interact with Slack data and workflows.
Windows MCP
MCP server for full computer use on Windows. Control mouse, keyboard, take screenshots, manage windows, and automate des
PAL MCP Server
Use Claude Code, Gemini CLI, Codex CLI, or any MCP client with any AI model. Acts as a multi-model proxy supporting Open
Deepcon
Deepcon is an AI coding assistant server offering up-to-date package docs via semantic search for smarter, faster AI pow
Screenshot Capture
Capture screenshots across macOS, Windows, and Linux using advanced screen capture and recording software for analysis,
I recommend Ollama for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Ollama is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Strong directory entry: Ollama surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Ollama is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated Ollama against two servers with overlapping tools; this profile had the clearer scope statement.
We wired Ollama into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We evaluated Ollama against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Ollama is the kind of server we cite when onboarding engineers to host + tool permissions.
Ollama has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired Ollama into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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Claude Desktop configuration
{
"mcpServers": {
"@rawveg/ollama-mcp": {
"command": "npx",
"args": [
"-y",
"@rawveg/ollama-mcp"
]
}
}
}Connects to your local Ollama installation to run AI models privately without cloud APIs. Lets you query models, list available models, and get model details.
Ollama is a community-built MCP server published by rawveg that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Ollama's local LLM models for secure, on-premise AI and data control with MCP-compatible apps. Deploy custom m It is categorized under ai ml, developer tools.
You can install Ollama in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
GitHub
MCP server for GitHub — enables Claude to interact with GitHub data and workflows.