mcp-local-analyst
Talk to your data locally 💬📊. A private AI Data Analyst built with the Model Context Protocol (MCP), Ollama, and SQLite. Turn natural language into SQL queries without data leaving your machine. Includes a Dockerized Streamlit UI
Install / Use
claude mcp add fabiothiroki -- npx -y github:fabiothiroki/mcp-local-analystIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of mcp-local-analyst
mcp-local-analyst scores 60/100 on our quality scale, 916th of 966 AI & Machine Learning skills we index.
Its MCP Server is 1.5 KB long, split into 5 sections and no code examples: moderately detailed.
It has 9 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 9 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- Our last check on 2026-09-12 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 86/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
mcp-local-analyst compared with similar skills
All 4 of these similar skills score higher than mcp-local-analyst; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| mcp-local-analyst (this skill)by fabiothiroki | 60 | 9 | 9mo ago | MCP Server |
| claude-memby thedotmack | 100 | 95.2k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 88.1k | 17d ago | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 85.0k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.3k | today | CLAUDE.md |
Frequently asked questions
- How do I install mcp-local-analyst?
- Run
claude mcp add fabiothiroki -- npx -y github:fabiothiroki/mcp-local-analyst. The install tabs above show the steps for each supported agent. - Which AI agents does mcp-local-analyst work with?
- It is written for Claude Code, Claude Desktop and Zed, as a MCP Server file. Other agents that read the same format can often use it too.
- Is mcp-local-analyst safe to use?
- It is MIT-licensed and scores 86/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is mcp-local-analyst still maintained?
- The repository was last updated about 9 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubMCP Local Analyst
Talk to your data locally 💬📊. A private AI Data Analyst built with the Model Context Protocol (MCP), Ollama, and SQLite. Turn natural language into SQL queries without data leaving your machine. Includes a Dockerized Streamlit UI
📝 Read the full article on Medium
Getting Started
Prerequisites
Before running the application, make sure you have the following installed:
-
Docker & Docker Compose - Required for running the application in containers
- Install Docker Desktop from docker.com
- Includes Docker Compose by default
-
Ollama - For running local LLM models
- Download from ollama.ai
- After installation, pull a model:
ollama pull mistral(or your preferred model) - Ollama will run as a service on
http://localhost:11434
Installation & Running Locally
-
Clone the repository
-
Ensure Ollama is running:
ollama serve(Keep this running in a separate terminal)
-
Start the application with Docker Compose:
docker-compose up --build -
Open your browser and navigate to:
http://localhost:8501
Configuration
- Modify the database by editing
src/seed_data.pyif needed - Configure model selection and parameters in the application UI
- Data is stored in the
data/directory
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.