Which Ollama models are supported?
Any model you have pulled locally (default is `llama3.1`). Override `OLLAMA_CHAT_MODEL` in `.env` to use a different one.
@tamdilip
Basic information
A minimal agentic app to interact with OLLAMA models leveraging multiple MCP server tools using BeeAI framework.
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A minimal client app that interacts with local Ollama models using multiple MCP (Model Context Protocol) agent tools, built with the BeeAI framework. It provides a chat interface where you can select MCP agents – such as Postgres or Fetch – and let the LLM reason and act on your requests.
Install Ollama, serve it locally, and pull at least one model (default: llama3.1). Configure your MCP servers in mcp-servers.json (defaults include Postgres and Fetch). Clone the repo, run npm i && npm start, then open http://localhost:3000. Use the UI dropdowns to choose a server and tool before asking questions.
.env)Any model you have pulled locally (default is `llama3.1`). Override `OLLAMA_CHAT_MODEL` in `.env` to use a different one.
Postgres and Fetch are pre‑configured. You can add any MCP server from the official examples by editing `mcp-servers.json`.
At least 16GB of RAM for models to perform well. Ollama must be installed and running, and Node.js/npm are needed to run the app.
Set `OLLAMA_BASE_URL` in `.env` (default: `http://localhost:11434/api`) to use a remote server instead of your local Ollama.
No. All interactions are local – the Ollama model runs on your machine and the MCP agents connect to local or remote services you configure.

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