Semantic Context Mcp

Created at 3 months ago

by zishengwu

A Model Context Protocol (MCP) server that leverages a vector database to efficiently index and query the codebase.

What is Semantic Context MCP?

Semantic Context MCP is a Model Context Protocol (MCP) server that utilizes a vector database to efficiently index and perform semantic searches across your codebase, allowing for natural language queries instead of just keyword matching.

How to use Semantic Context MCP?

To use the Semantic Context MCP, clone the repository from GitHub, configure the MCP JSON file in your IDE with the necessary environment variables, and run the server using the provided command.

Key features of Semantic Context MCP?

Incremental indexing using a Merkle Tree for efficient updates.
Multi-language support through AST parsing.
Semantic code search capabilities.
Background automation for periodic updates.
Simple MCP interface for integration with other systems.

Use cases of Semantic Context MCP?

Finding relevant code snippets using natural language queries.
Tracking changes in codebases efficiently.
Supporting multiple programming languages for diverse projects.

FAQ from Semantic Context MCP?

What programming languages does it support?

It supports a wide range of languages including Python, Java, C++, JavaScript, TypeScript, and Go.

How does it handle file changes?

It uses a Merkle Tree to detect changes and only re-indexes modified files, ensuring efficiency.

Is it easy to integrate with existing systems?

Yes, it provides a simple interface for integration.

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