MCP Server: Ollama Deep Researcher
by Cam10001110101
This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides deep research capabilities as MCP tools, enabling AI assistants to perform in-depth research on topics using local LLMs via Ollama.
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What is MCP Server: Ollama Deep Researcher?
The MCP Server: Ollama Deep Researcher is an MCP server that leverages local LLMs hosted by Ollama to provide deep research capabilities. It allows AI assistants to perform in-depth research on a given topic by iteratively generating search queries, summarizing search results, and reflecting on knowledge gaps.
How to use MCP Server: Ollama Deep Researcher?
To use this server, you need to install Node.js, Python, and Ollama. You can either install the server directly or use Docker. After installation, configure your MCP client (e.g., Claude Desktop App or Cline) to connect to the server. You will also need API keys for Tavily, Perplexity, and LangSmith. You can then use the available tools (configure, research, get_status) via the MCP client to perform research on specified topics.
Key features of MCP Server: Ollama Deep Researcher
Iterative research process with multiple cycles
Integration with local LLMs via Ollama
Web search using Tavily or Perplexity API
Automatic storage of research results as MCP resources
Tracing and monitoring with LangSmith
Use cases of MCP Server: Ollama Deep Researcher
In-depth research on specific topics
Generating comprehensive summaries with citations
Identifying knowledge gaps and refining search queries
Integrating research results into AI assistant conversations
Automating research workflows for AI agents
FAQ from MCP Server: Ollama Deep Researcher
What are the prerequisites for running this server?
What are the prerequisites for running this server?
You need Node.js, Python 3.10 or higher, Ollama, and API keys for Tavily, Perplexity, and LangSmith. You also need a machine capable of running your selected Ollama model with at least 8GB of RAM.
How do I install the server?
How do I install the server?
You can install the server directly by cloning the repository, installing dependencies with npm and uv (or pip), building the TypeScript code, and pulling a local LLM from Ollama. Alternatively, you can use Docker for a simplified setup.
How do I configure the MCP client?
How do I configure the MCP client?
You need to add the server to your MCP client configuration file (e.g., claude_desktop_config.json or cline_mcp_settings.json) with the appropriate command, arguments, and environment variables. The configuration differs slightly depending on whether you are using a standard installation or Docker.
What is LangSmith used for?
What is LangSmith used for?
LangSmith is used for tracing and monitoring the research process, including LLM interactions, web search operations, and research workflow steps. It provides insights into performance, debugging, and optimization.
How do I troubleshoot common issues?
How do I troubleshoot common issues?
Refer to the Troubleshooting section in the README for solutions to common issues such as Ollama connection problems, API key issues, MCP server issues, Docker issues, build issues, and Python issues. Use the MCP Inspector for debugging.