Mcp Ollama File Agent
What is Mcp Ollama File Agent
mcp-ollama-file-agent is a local AI agent that utilizes the Model Context Protocol (MCP) to interact with local filesystems, enabling advanced functionalities such as file summarization and tool usage.
Use cases
Use cases include summarizing reports from local files, automating data extraction from documents, enhancing productivity in software development by providing AI assistance, and creating interactive applications with a user-friendly interface.
How to use
To use mcp-ollama-file-agent, run the Docker container using the command ‘docker-compose up --build’. Access the Streamlit UI at http://localhost:8501 to interact with the agent and view outputs in the terminal.
Key features
Key features include the ability to run local large language models (LLMs) like qwen2:7b, mistral, and phi3, enable tool use via MCP, fetch and summarize files, and a fully Dockerized setup for offline capabilities.
Where to use
mcp-ollama-file-agent can be used in various fields such as data analysis, document summarization, software development, and any application requiring local file interaction and AI capabilities.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp Ollama File Agent
mcp-ollama-file-agent is a local AI agent that utilizes the Model Context Protocol (MCP) to interact with local filesystems, enabling advanced functionalities such as file summarization and tool usage.
Use cases
Use cases include summarizing reports from local files, automating data extraction from documents, enhancing productivity in software development by providing AI assistance, and creating interactive applications with a user-friendly interface.
How to use
To use mcp-ollama-file-agent, run the Docker container using the command ‘docker-compose up --build’. Access the Streamlit UI at http://localhost:8501 to interact with the agent and view outputs in the terminal.
Key features
Key features include the ability to run local large language models (LLMs) like qwen2:7b, mistral, and phi3, enable tool use via MCP, fetch and summarize files, and a fully Dockerized setup for offline capabilities.
Where to use
mcp-ollama-file-agent can be used in various fields such as data analysis, document summarization, software development, and any application requiring local file interaction and AI capabilities.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
🧠 Ollama MCP Local Agent
Local AI Agents with Tool Use (Filesystem) Powered by Ollama + LangChain + MCP
🚀 Features
- Run local LLMs like
qwen2:7b,mistral,phi3, etc. - Enable tool use via Model Context Protocol (MCP)
- Fetch and summarize files from your filesystem
- Streamlit UI + Python Agent
- Fully Dockerized & offline-capable
📦 Project Structure
. ├── agent_runner.py ├── file_tool.py ├── mcp-tool.json ├── streamlit_app.py ├── Dockerfile ├── Dockerfile.agent ├── docker-compose.yml ├── docs/ │ └── example.txt ├── .gitignore └── README.md
🐳 Run with Docker
docker-compose up --build
- Visit Streamlit: http://localhost:8501
- Agent output shown in terminal
- MCP API: http://localhost:3333/docs
📜 License
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
