Ollama PostgreSQL Data Analysis
This MCP implementation provides an interactive chat interface that combines Ollama's LLM capabilities with PostgreSQL database access. Built with TypeScript and leveraging the Model Context Protocol, it enables natural language querying of SQL databases. The system automatically generates SQL queries based on user input, executes them through a secure, read-only connection, and returns AI-interpreted results. Key features include schema-aware responses and support for the qwen2.5-coder:7b-instruct model. This implementation is particularly useful for data analysts, business users, and developers who need to quickly extract insights from PostgreSQL databases without writing SQL queries manually.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/robdodson/ollama-mcp-db
- Author type
- human
- Updated
- 2026-06-11
Use via MCP
Resolve Ollama PostgreSQL Data Analysis from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.