agent-lsp

agent-lsp makes code operations reliable for AI agents.

It is a stateful runtime over real language servers, not a bridge. It keeps the language server's semantic index warm and adds a skill layer that turns multi-step code operations into single, correct workflows.

Most MCP-LSP tools fail in practice:

• Stateless bridges — no session, no context, no cross-file awareness
• Raw tools — agents skip steps or use them incorrectly

The tools exist. The workflow doesn't reliably happen.

agent-lsp fixes both. The persistent session indexes your workspace once and keeps it warm. The skill layer encodes correct tool sequences so workflows actually happen.

Example: call /lsp-rename and it will validate the rename, preview all affected files, show diagnostic impact, and apply atomically. One command. No missed steps.

50 tools. 49 CI-verified end-to-end. 30 languages. Built to LSP 3.17 spec.

Work across all your projects in one session. Point your AI at ~/code/. One agent-lsp process routes .go to gopls, .ts to typescript-language-server, .py to pyright — no reconfiguration when you switch projects.

Skills

Raw tools get ignored. Skills get used. Each skill encodes the correct tool sequence so workflows actually happen without per-prompt orchestration instructions.

cd skills && ./install.sh

Docker

# Go
docker run --rm -i -v /your/project:/workspace ghcr.io/blackwell-systems/agent-lsp:go go:gopls

# TypeScript
docker run --rm -i -v /your/project:/workspace ghcr.io/blackwell-systems/agent-lsp:typescript typescript:typescript-language-server,--stdio

# Python
docker run --rm -i -v /your/project:/workspace ghcr.io/blackwell-systems/agent-lsp:python python:pyright-langserver,--stdio

Images are also mirrored to Docker Hub (blackwellsystems/agent-lsp). See DOCKER.md for full tag list and docker-compose setup.

Installation

# curl | sh (Linux / macOS)
curl -fsSL https://raw.githubusercontent.com/blackw

... [View full README on GitHub](https://github.com/blackwell-systems/agent-lsp#readme)