agent-lsp
A stateful LSP runtime for AI agents: warm language server sessions with 50+ tools for go-to-definition, find-references, diagnostics, rename, and more across 30+ languages.
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.
curl -fsSL https://raw.githubusercontent.com/blackwell-systems/agent-lsp/main/install.sh | sh
agent-lsp init
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.
See docs/skills.md for full descriptions and usage guidance.
Before you change anything
| Skill | Purpose |
|---|---|
/lsp-impact | Blast-radius analysis before touching a symbol or file |
/lsp-implement | Find all concrete implementations of an interface |
/lsp-dead-code | Detect zero-reference exports before cleanup |
Editing safely
| Skill | Purpose |
|---|---|
/lsp-safe-edit | Speculative preview before disk write; before/after diagnostic diff; surfaces code actions on errors |
/lsp-simulate | Test changes in-memory without touching the file |
/lsp-edit-symbol | Edit a named symbol without knowing its file or position |
/lsp-edit-export | Safe editing of exported symbols — finds all callers first |
/lsp-rename | prepare_rename safety gate, preview all sites, confirm, apply atomically |
Understanding unfamiliar code
| Skill | Purpose |
|---|---|
/lsp-explore | "Tell me about this symbol": hover + implementations + call hierarchy + references in one pass |
/lsp-understand | Deep-dive Code Map for a symbol or file: type info, call hierarchy, references, source |
/lsp-docs | Three-tier documentation: hover → offline toolchain → source |
/lsp-cross-repo | Find all usages of a library symbol across consumer repos |
/lsp-local-symbols | File-scoped symbol list, usage search, and type info |
After editing
| Skill | Purpose |
|---|---|
/lsp-verify | Diagnostics + build + tests after every edit |
/lsp-fix-all | Apply quick-fix code actions for all diagnostics in a file |
/lsp-test-correlation | Find and run only tests that cover an edited file |
/lsp-format-code | Format a file or selection via the language server formatter |
Generating code
| Skill | Purpose |
|---|---|
/lsp-generate | Trigger server-side code generation (interface stubs, test skeletons, mocks) |
/lsp-extract-function | Extract a code block into a named function via code actions |
Full workflow
| Skill | Purpose |
|---|---|
/lsp-refactor | End-to-end refactor: blast-radius → preview → apply → verify → test |
cd skills && ./install.sh
Docker
Stdio mode (MCP client spawns the container directly):
# 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
HTTP mode (persistent service, remote clients connect over HTTP+SSE):
docker run --rm \
-p 8080:8080 \
-v /your/project:/workspace \
-e AGENT_LSP_TOKEN=your-secret-token \
ghcr.io/blackwell-systems/agent-lsp:go \
--http --port 8080 go:gopls
Images run as a non-root user (uid 65532) by default. Set AGENT_LSP_TOKEN via environment variable — never --token on the command line. Images are also mirrored to Docker Hub (blackwellsystems/agent-lsp). See DOCKER.md for the full tag list, HTTP mode setup, and security hardening options.
Installation
macOS / Linux
# curl | sh
curl -fsSL https://raw.githubusercontent.com/blackwell-systems/agent-lsp/main/install.sh | sh
# Homebrew
brew install blackwell-systems/tap/agent-lsp
Windows
# PowerShell (no admin required)
iwr -useb https://raw.githubusercontent.com/blackwell-systems/agent-lsp/main/install.ps1 | iex
# Scoop
scoop bucket add blackwell-systems https://github.com/blackwell-systems/agent-lsp
scoop install blackwell-systems/agent-lsp
# Winget
winget install BlackwellSystems.agent-lsp
All platforms
# npm
npm install -g @blackwell-systems/agent-lsp
# Go install
go install github.com/blackwell-systems/agent-lsp@latest
Quick start
agent-lsp init
Detects language servers on your PATH, asks which AI tool you use, and writes the correct MCP config. For CI or scripted use: agent-lsp init --non-interactive.
Setup
Step 1: Install language servers
Install the servers for your stack. Common ones:
| Language | Server | Install |
|---|---|---|
| TypeScript / JavaScript | typescript-language-server | npm i -g typescript-language-server typescript |
| Python | pyright-langserver | npm i -g pyright |
| Go | gopls | go install golang.org/x/tools/gopls@latest |
| Rust | rust-analyzer | rustup component add rust-analyzer |
| C / C++ | clangd | apt install clangd / brew install llvm |
| Ruby | solargraph | gem install solargraph |
Full list of 30 supported languages in docs/language-support.md.
Step 2: Add to your AI config
{
"mcpServers": {
"lsp": {
"type": "stdio",
"command": "agent-lsp",
"args": [
"go:gopls",
"typescript:typescript-language-server,--stdio",
"python:pyright-langserver,--stdio"
]
}
}
}
Each arg is language:server-binary (comma-separate server args).
Step 3: Start working
start_lsp(root_dir="/your/project")
Then use any of the 50 tools. The session stays warm; no restart needed when switching files.
Why agent-lsp
| agent-lsp | other MCP-LSP implementations | |
|---|---|---|
| Languages (CI-verified) | 30 (end-to-end integration tests) | config-listed, untested |
| Tools | 50 | 3–18 |
| Multi-server routing | ✓ (one process, many languages) | varies |
| LSP spec compliance | 3.17, built to spec | ad hoc |
| Connection model | persistent (warm index) | per-request or cold-start |
| Cross-file references | ✓ | rarely |
| Real-time diagnostic subscriptions | ✓ | ✗ |
| Semantic token classification | ✓ | ✗ (only one competitor) |
| Call hierarchy | ✓ (single tool, direction param) | ✗ or 3 separate tools |
| Type hierarchy | ✓ (single tool, direction param) | ✗ or untested |
| Fuzzy position fallback | ✓ | ✗ or partial |
| Auto-watch (index stays fresh) | ✓ (always-on, debounced) | ✗ (manual notify required) |
| Multi-root / cross-repo | ✓ (add_workspace_folder) | ✗ or single-workspace only |
| HTTP+SSE transport | ✓ (bearer token auth, timeouts, non-root Docker) | ✗ or experimental |
| Distribution | single Go binary | Node.js or Bun runtime required |
Use Cases
- Multi-project sessions: point your AI at
~/code/, work across any project without reconfiguring - Polyglot development: Go backend + TypeScript frontend + Python scripts in one session
- Large monorepos: one server handles all languages, routes by file extension
- Code migration: refactor across repos with full cross-repo reference tracking
- CI pipelines: validate against real language server behavior
Multi-Language Support
30 languages, CI-verified end-to-end against real language servers on every CI run. No other MCP-LSP implementation has an equivalent test matrix.
See docs/language-support.md for the full coverage matrix and per-language CI notes.
Tools
50 tools covering navigation, analysis, refactoring, speculative execution, and session lifecycle. All CI-verified.
See docs/tools.md for the full reference with parameters and examples.
Further reading
- docs/skills.md — skill reference: workflows, use cases, and composition
- docs/tools.md — full tool reference
- docs/language-support.md — language coverage matrix
- docs/speculative-execution.md — simulate-before-apply workflows
- docs/lsp-conformance.md — LSP 3.17 spec coverage
- docs/architecture.md — Go package structure and internals
- docs/ci-notes.md — CI quirks and test harness details
- docs/distribution.md — install channels and release pipeline
- DOCKER.md — Docker tags, compose, and volume caching
Development
git clone https://github.com/blackwell-systems/agent-lsp.git
cd agent-lsp && go build ./...
go test ./... # unit tests
go test ./... -tags integration # integration tests (requires language servers)
Library Usage
The pkg/lsp, pkg/session, and pkg/types packages expose a stable Go API for using agent-lsp's LSP client directly without running the MCP server.
import "github.com/blackwell-systems/agent-lsp/pkg/lsp"
client := lsp.NewLSPClient("gopls", []string{})
client.Initialize(ctx, "/path/to/workspace")
defer client.Shutdown(ctx)
locs, err := client.GetDefinition(ctx, fileURI, lsp.Position{Line: 10, Character: 4})
See docs/architecture.md for the full package API.
License
MIT
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