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
AWS Web Search
Current, cited web results for Claude from an Amazon-operated web index, served through your own AWS account.
Fullstory
Product analytics with receipts. Build segments, compute metrics, and analyze conversions from your Fullstory behavioral data. Then pull the real sessions to back it up.
Sent
Send and manage customer messages across SMS, WhatsApp, and RCS. Build and manage production messaging agents and workflows.
Plotly Cloud
Build and deploy Plotly Dash apps to Plotly Cloud from a conversation with Claude.
MuuMuu Domain byGMO Pepabo
ムームードメインと接続し、ドメインの空き検索・価格確認から購入手続きまでを会話で進められます。決済はムームードメインのサイト上でご自身が完了させる方式です。保有ドメインの一覧・詳細確認、ネームサーバーの確認・変更、DNSレコードの一覧・作成・更新・削除、更新日や自動更新設定の確認・変更にも対応します。
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.