Srclight
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Deep code indexing for AI agents — 25 MCP tools: hybrid FTS5 + embedding search, call graphs, git blame/hotspots, build system analysis. Multi-repo workspaces, GPU-accelerated semantic search, 10 languages. Fully local, zero cloud dependencies.
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Setup
Install Srclight in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/srclight/srclight
Follow the installation instructions in the repository README, then restart your MCP client.
Deep code indexing for AI agents.SQLite FTS5 + tree-sitter + embeddings + MCP.
Srclight builds a rich, searchable index of your codebase that AI coding agents can query instantly — replacing dozens of grep/glob calls with precise, structured lookups. It is the most comprehensive code intelligence MCP server available: 42 tools covering symbol search, relationship graphs, community detection, impact analysis, git change intelligence, semantic search, build system awareness, and document extraction — capabilities no other single MCP server combines. Fully local and private: your code never leaves your machine.
AI coding agents (Claude Code, Cursor, etc.) spend40-60% of their tokens on orientation— searching for files, reading code to understand structure, hunting for callers and callees. Srclight eliminates this waste.
- Minimal dependencies— single SQLite file per repo, no Docker/Redis/vector DB
- Fully offline— no API calls, works air-gapped (Ollama local embeddings)
- Incremental— only re-indexes changed files (content hash detection)
- 11 languages— Python, C, C++, C#, JavaScript, TypeScript, PHP, Dart, Swift, Kotlin, Java, Go
- 10 document formats— PDF, DOCX, XLSX, HTML, CSV/TSV, email (.eml), images (PNG/JPG/SVG/etc.), plain text, RST, Markdown
- Optional OCR— PaddleOCR for scanned/image-only PDF pages; pytesseract for images
- 4 search modes— symbol names, source code (trigram), documentation (stemmed), semantic (embeddings)
- Hybrid search— RRF fusion of keyword + semantic results for best accuracy
- Multi-repo workspaces— search across all your repos simultaneously via SQLite ATTACH+UNION
- MCP server— works with Claude Code, Cursor, and any MCP client
- CLI— index, search, and inspect from the terminal
- Auto-reindex— git post-commit/post-checkout hooks keep indexes fresh
- Python 3.11+
- Git(for change intelligence and auto-reindex hooks)
- Ollama(optional, for semantic search / embeddings) —ollama.com
- NVIDIA GPU + cupy(optional, for GPU-accelerated vector search)
- Poppler(optional, for PaddleOCR scanned-PDF support) —apt install poppler-utils/brew install poppler
# Install from PyPI pip install srclight # Install from source git clone https://github.com/srclight/srclight.git cd srclight pip install -e . # Optional: document format support (PDF, DOCX, XLSX, HTML, images) pip install 'srclight[docs,pdf]' # Optional: OCR for scanned PDFs (also needs poppler-utils on your system) pip install 'srclight[pdf,paddleocr]' # Optional: OCR for images (needs tesseract on your system) pip install 'srclight[docs,ocr]' # Optional: GPU-accelerated vector search (requires CUDA 12.x) pip install 'srclight[gpu]' # Everything (docs + pdf + ocr + paddleocr + gpu) pip install 'srclight[all]' # Index your project cd /path/to/your/project srclight index # Index with embeddings (requires Ollama running) srclight index --embed qwen3-embedding # Search srclight search "lookup" srclight search --kind function "parse" srclight symbols src/main.py # Start MCP server (for Claude Code / Cursor) srclight serve
Note:srclight indexautomatically adds.srclight/to your.gitignore. Index databases and embedding files can be large and should never be committed.
Srclight supports embedding-based semantic search for natural language queries like "find code that handles authentication" or "where is the database connection pool".
# Install Ollama (https://ollama.com) # Pull an embedding model ollama pull qwen3-embedding # Best quality (8B params, needs ~6GB VRAM) ollama pull nomic-embed-text # Lighter alternative (137M params) # Index with embeddings srclight index --embed qwen3-embedding # Or index workspace with embeddings srclight workspace index -w myworkspace --embed qwen3-embedding
- Each symbol's name + signature + docstring + content is embedded as a float vector
- Vectors are stored as BLOBs insymbol_embeddingstable (SQLite)
- After indexing, a.npysidecar snapshot is built and loaded toGPU VRAM(cupy) or CPU RAM (numpy) for fast search
- semantic_search(query)embeds the query and runs cosine similarity against the GPU-resident matrix (~3ms for 27K vectors on a modern GPU)
- hybrid_search(query)combines FTS5 keyword results + embedding results via Reciprocal Rank Fusion (RRF)
# Use Voyage Code 3 (API, highest quality) VOYAGE_API_KEY=your-key srclight index --embed voyage-code-3
Embeddings are stored insymbol_embeddingstable in.srclight/index.db. After indexing, a.npysidecar snapshot is built for fast GPU loading:
For ~27K symbols at 4096 dims (qwen3-embedding), that's ~428 MB on disk, ~450 MB in VRAM. Incremental: only re-embeds symbols whose content changed; sidecar rebuilt after each indexing run.
Search across multiple repos simultaneously. Each repo keeps its own.srclight/index.db; at query time, srclight ATTACHes them all and UNIONs across schemas.
# Create a workspace srclight workspace init myworkspace # Add repos srclight workspace add /path/to/repo1 -w myworkspace srclight workspace add /path/to/repo2 -w myworkspace -n custom-name # Index all repos (with optional embeddings) srclight workspace index -w myworkspace srclight workspace index -w myworkspace --embed qwen3-embedding # Search across all repos srclight workspace search "Dictionary" -w myworkspace srclight workspace search "Dictionary" -w myworkspace --project repo1 # Status srclight workspace status -w myworkspace srclight workspace list # Start MCP server in workspace mode srclight serve --workspace myworkspace
Git submodulesare not indexed automatically —git ls-filesdoes not recurse into them. To index a submodule, clone it separately and add it as its own workspace project. Seedocs/usage-guide.mdfor details.
Srclight supports two transport modes:stdio(one server per session) andSSE(persistent server, multiple sessions). SSE is recommended for workspaces.
Stdio (simplest — one server per session):
# Single repo claude mcp add srclight -- srclight serve # Workspace mode claude mcp add srclight -- srclight serve --workspace myworkspace # Make it available in all projects (user scope) claude mcp add --scope user srclight -- srclight serve --workspace myworkspace
SSE (persistent server — recommended for workspaces):
Run srclight as a long-lived server, then point Claude Code at it:
# Start the server (default: http://127.0.0.1:8742/sse) srclight serve --workspace myworkspace & # Or install as a systemd user service (Linux/WSL) # See docs/usage-guide.md for the service file # Connect Claude Code to the running server claude mcp add --transport sse srclight http://127.0.0.1:8742/sse
SSE mode supports multiple concurrent sessions and survives Claude Code restarts.
SSE (recommended):Run srclight once, then connect Cursor to it. Best for responsiveness and no cold-start per session.
Start the server:srclight serve --workspace myworkspace(default SSE on port 8742).
- UI:Settings → Tools & MCP → Add new MCP server → Type:streamableHttp, URL:http://127.0.0.1:8742/sse.
- JSON(project.cursor/mcp.jsonor global~/.cursor/mcp.json):
"srclight": { "url": "http://127.0.0.1:8742/sse" }
Stdio (alternative):One server process per Cursor session.
- UI:Type:command, Command:srclight, Args:serve --workspace myworkspace(orservefor single-repo).
- JSON:
"srclight": { "command": "srclight", "args": ["serve", "--workspace", "myworkspace"] }
For single-repo:"args": ["serve"]. Restart Cursor completely after adding the server.
Verify:In Cursor chat, ask "What projects are in the srclight workspace?" or "List srclight tools" — the agent should calllist_projects()or show srclight tools.
OpenClaw connects to srclight viamcporter, its built-in MCP tool server CLI.
# 1. Add srclight to mcporter's home config mcporter config add srclight http://127.0.0.1:8742/sse \ --transport sse --scope home \ --description "Srclight deep code indexing" # 2. Verify the connection mcporter call srclight.list_projects # 3. Restart the OpenClaw gateway to pick up the new server systemctl --user restart openclaw-gateway # if using systemd # or: openclaw daemon restart
The OpenClaw agent can then use srclight tools via themcporterskill:
mcporter call srclight.search_symbols query="my_function" mcporter call srclight.get_callers symbol_name="MyClass" project="my-repo" mcporter call srclight.hybrid_search query="authentication logic"
Prerequisite:Srclight must be running as an SSE server (see above). OpenClaw's mcporter connects over HTTP — stdio mode is not supported.
Claude Desktop (claude_desktop_config.json)
{ "mcpServers": { "srclight": { "command": "srclight", "args": ["serve", "--workspace", "myworkspace"] } } }
Any MCP-compatible client can connect to the SSE endpoint:
Srclight exposes 42 MCP tools organized in seven tiers. The MCP server includes built-in instructions that guide AI agents on which tool to use and when — agents receive a session protocol, tool selection guide, andprojectparameter documentation automatically on connection.
Tier 2b: Community & Impact Analysis
In workspace mode,search_symbols,get_symbol,codebase_map, andhybrid_searchaccept an optionalprojectfilter. Graph/git/build/community tools requireprojectin workspace mode.
Seedocs/usage-guide.mdfor the full deployment and usage guide, including:
- Setting up srclight as a global MCP server for Claude Code
- Adding/removing repos from workspaces
- What happens on commits and branch switches
- Re-embedding workflows
- Troubleshooting
# Install post-commit + post-checkout hooks in current repo srclight hook install # Install across all repos in a workspace srclight hook install --workspace myworkspace # Remove hooks srclight hook uninstall
The hooks runsrclight indexin the background after each commit and branch switch.
- tree-sitterparses every source file into an AST
- Document extractorshandle non-code files (PDF, DOCX, XLSX, HTML, CSV, images, email, text) — extracting headings, tables, pages, and metadata as searchable symbols. Scanned PDF pages are optionally OCR'd via PaddleOCR.
- Symbols (functions, classes, methods, structs, etc.) are extracted with full metadata
- ThreeSQLite FTS5indexes are built with different tokenization strategies:
- Names: code-aware tokenization (splitscamelCase, handles::,->)
- Content: trigram index for substring matching
- Docs: Porter stemming for natural language in docstrings
repo1/.srclight/index.db ──┐ repo2/.srclight/index.db ──┼── ATTACH ──→ :memory: ──→ UNION ALL queries repo3/.srclight/index.db ──┘
Each repo is indexed independently. At query time, SQLite's ATTACH mechanism joins them into a single searchable namespace. Handles >10 repos via automatic batching (SQLite's ATTACH limit).
A survey of 50+ MCP code intelligence servers across all major registries (Official MCP Registry, Smithery, Glama, mcp.so, awesome-mcp-servers) found that no other single server combines srclight's full capabilities:
Unlike grep-based tools, srclight builds a persistent index with structured lookups. Unlike cloud-based solutions, everything runs locally — your code never leaves your machine. Unlike IDE plugins, srclight works with any MCP client.
- Symbol intelligence + 3x FTS5 search
- Relationship graph: callers, callees, hierarchy
- Blast radius, test discovery, implementors
- Git change intelligence: blame, hotspots, recent changes
- Build system awareness: CMake, .csproj, platform conditionals
- Semantic search: embeddings via Ollama/Voyage, hybrid RRF
- GPU-accelerated vector search:.npysidecar, cupy/numpy vectorized math
- Multi-repo workspaces (ATTACH+UNION)
- Auto-reindex git hooks (post-commit + post-checkout)
- Document extraction: PDF, DOCX, XLSX, HTML, CSV, email, images, text (heading detection, tables, metadata)
- Optional OCR: PaddleOCR for scanned PDFs, pytesseract for images
- MCP agent guidance: comprehensive instructions, tool selection guide, session protocol
- Workspace config hot-reload (no server restart needed to add repos)
- VectorCache sidecar re-discovery (no restart needed after embedding)
- Project name suggestions in error messages
- Community detection: Louvain clustering on call-graph edges with TF-IDF auto-labeling
- Execution flow tracing: BFS from entry points across community boundaries
- Impact analysis: per-symbol blast radius with risk scoring (LOW/MEDIUM/HIGH/CRITICAL)
- detect_changes: map git diff to affected symbols and aggregate blast radius
- Cross-language concept mapping (explicit edges between equivalent symbols across languages)
- Pattern intelligence (convention detection, coding pattern extraction)
- AI pre-computation (symbol summaries via cheap LLM)
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