CodeSynapse MCP Server

@Poytr1

Basic information

About CodeSynapse MCP Server

An MCP (Model Context Protocol) server that integrates with the Language Server Protocol (LSP) to expose rich semantic information from codebases to an LLM code agent.

#code-synapse#mcp #language-server

CodeSynapse MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

CodeSynapse MCP Server tools

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Overview

What is CodeSynapse?

CodeSynapse is an MCP server that integrates with the Language Server Protocol (LSP) to expose rich semantic information from codebases to LLM code agents. It supports multiple programming languages through a configuration registry that maps file types or language identifiers to their respective language servers.

How to use CodeSynapse?

Configure CodeSynapse by providing a registry that maps file types (e.g., .py, .ts) to their respective language servers (e.g., Pyright for Python, tsserver for TypeScript). The server then handles LSP queries and makes semantic context available via the MCP interface.

Key features of CodeSynapse

Integrates with Language Server Protocol (LSP)
Exposes semantic code information to LLM agents
Supports multiple programming languages
Uses a configuration registry for file‑type to language‑server mapping
Example mappings: Python via Pyright, TypeScript via tsserver

Use cases of CodeSynapse

An AI coding assistant queries definitions, references, and completions for symbols.
Automated code review retrieves semantic context for static analysis.
Multi‑language IDE plugins use MCP to fetch LSP data for any supported language.

Frequently asked questions

What is CodeSynapse’s relationship to LSP?

CodeSynapse acts as a bridge between MCP and the Language Server Protocol, translating LSP responses into semantic data consumable by an LLM agent.

Which programming languages does CodeSynapse support?

It supports any language for which a language server is registered in the configuration registry. Built‑in examples include Python (using Pyright) and TypeScript (using tsserver).

How does CodeSynapse decide which language server to use?

It uses a configuration registry that maps file extensions or language identifiers to the appropriate language server executable.

Where does the semantic data come from?

The data originates from the configured language server, which performs static analysis of the codebase and returns results like definitions, references, and diagnostics.

Are there any runtime dependencies besides CodeSynapse itself?

Yes, the corresponding language servers (e.g., Pyright for Python, tsserver for TypeScript) must be installed and accessible on the system for each language you want to analyze.

Comments

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