dlang_mcp 1.0.0

dlang_mcp - D Language MCP Server

MCP (Model Context Protocol) server for D language tools with semantic package search.

Status

• mostly vibe coded in a day
• only tested on linux
• PR's welcome
• actually not really sure if correctly used by the LLM or really useful
• if you have something better, please tell me

Features (20 MCP Tools)

Code Quality & Analysis

• dscanner — Static analysis for bugs, style issues, and complexity. Supports multiple modes: lint (default), syntax validation, import listing, line counts, AST generation, and ctags output. Configurable check presets (default, strict, minimal).
• dfmt — Format D source code with configurable brace style (allman, otbs, stroustrup), indentation, and line length. Paste code in, get formatted code back.
• compile_check — Compile-check D code without linking or running. Catches type errors, undefined identifiers, and syntax errors. Accepts inline code or a file path; set dub_project for automatic import path resolution. Supports dmd and ldc2.
• coverage_analysis — Analyze code coverage from .lst files produced by dmd -cov or ldc2 --cov. Reports per-function coverage stats sorted by most uncovered lines. Point it at a single file or a directory to scan all .lst files.

Build, Test & Run

• build_project — Build a D/dub project and get structured results: success/failure, compiler errors with file/line/message, and warnings. Supports debug/release builds, compiler selection (dmd/ldc2), and force rebuild.
• run_tests — Run unit tests for a D/dub project. Returns pass/fail count, test output, and compiler errors if the build fails. Supports test name filtering and verbose output.
• run_project — Build and execute a D/dub project, returning stdout, stderr, and exit code. Pass arguments through to the built program.

Package & Dependency Management

• fetch_package — Download a D package from the dub registry to the local cache. Optionally specify a version.
• upgrade_dependencies — Upgrade project dependencies to their latest allowed versions. Supports missing_only (fetch without upgrading) and verify (check consistency without modifying).
• analyze_project — Analyze a D/dub project's build configuration: project name, dependency versions, source files, import paths, and build settings. Uses dub describe with fallback to direct file parsing.

Code Navigation & Structure

• ctags_search — Search for symbol definitions (functions, classes, structs, enums) by name across a project. Supports exact, prefix, and regex matching with kind filtering. Auto-generates the tags file when needed.
• get_module_outline — Get a hierarchical outline of every symbol in a D source file: names, kinds, line numbers, visibility, attributes (@safe, @nogc, nothrow, pure), return types, parameters, and ddoc comments. Accepts a file path or inline code.
• list_project_modules — List all modules in a project with summaries of their public APIs (functions, classes, structs, enums with signatures).
• ddoc_analyze — Analyze documentation coverage and attribute usage across a project using DMD's JSON output. Reports per-module doc coverage percentages, function/type counts, and template statistics.

Semantic Search (requires indexed database)

These tools search a local SQLite database of indexed D packages. Use --ingest to populate the database, and optionally enable ONNX neural embeddings or sqlite-vec vector similarity for better results (see Semantic Search Setup).

• search_packages — Search indexed D packages by name, description, or tags. Find libraries for a given task.
• search_functions — Search function definitions by name, signature, or description across all indexed packages. Find how to do things in D.
• search_types — Search type definitions (classes, structs, interfaces, enums) by name or description. Filter by kind.
• search_examples — Search for runnable D code examples by description or code pattern. Returns complete snippets with required imports.
• get_imports — Look up the required import statements for D symbols. Pass a symbol name, get back the import line.

Diagnostics

• get_feature_status — Check which optional runtime features are available: database, ONNX embeddings, sqlite-vec, external tools (dscanner, dfmt), and active search mode. Useful for diagnosing issues.

Quick Start

Prerequisites

• DMD 2.100+ or LDC
• dub package manager
• dscanner and dfmt (for code analysis tools)
• SQLite 3.40+ with FTS5 support

Build

dub build

One-Command Setup

chmod +x setup.sh && ./setup.sh

This builds the project, installs optional components (sqlite-vec, ONNX), and ingests example packages. Use --skip-onnx for a minimal TF-IDF-only setup, or --skip-packages to skip package ingestion.

Minimal Manual Setup

# 1. Build
dub build

# 2. Initialize database
./bin/dlang_mcp --init-db

# 3. Ingest some packages
./bin/dlang_mcp --ingest --package=phobos
./bin/dlang_mcp --ingest --package=intel-intrinsics

# 4. Train TF-IDF embeddings
./bin/dlang_mcp --train-embeddings

# 5. Run the MCP server
./bin/dlang_mcp

For semantic search with neural embeddings (ONNX) or vector similarity (sqlite-vec), see Semantic Search Setup below.

MCP Client Configuration

Claude Desktop

Add to ~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "dlang": {
      "command": "/path/to/dlang_mcp/bin/dlang_mcp"
    }
  }
}

opencode

Add to ~/.config/opencode/opencode.json:

{
  "mcp": {
    "dlang-mcp": {
      "type": "local",
      "command": ["/path/to/dlang_mcp/bin/dlang_mcp"],
      "enabled": true
    }
  }
}

GitHub Copilot (VS Code)

Add to .vscode/mcp.json in your workspace:

{
  "servers": {
    "dlang-mcp": {
      "type": "stdio",
      "command": "/path/to/dlang_mcp/bin/dlang_mcp"
    }
  }
}

GitHub Copilot CLI

Add to ~/.config/github-copilot/github-copilot-cli/mcp.json:

{
  "servers": {
    "dlang-mcp": {
      "type": "stdio",
      "command": "/path/to/dlang_mcp/bin/dlang_mcp"
    }
  }
}

OpenAI Codex CLI

Add to ~/.codex/config.json:

{
  "mcpServers": {
    "dlang-mcp": {
      "type": "stdio",
      "command": "/path/to/dlang_mcp/bin/dlang_mcp"
    }
  }
}

Zed

Add to ~/.config/zed/settings.json:

{
  "context_servers": {
    "dlang-mcp": {
      "command": {
        "path": "/path/to/dlang_mcp/bin/dlang_mcp",
        "args": []
      },
      "settings": {}
    }
  }
}

Command Line Reference

# Run as MCP server over stdio (default)
./bin/dlang_mcp

# Run as MCP server over HTTP (SSE + streamable endpoints)
./bin/dlang_mcp --http --port=3000 --host=127.0.0.1

# Initialize the search database
./bin/dlang_mcp --init-db

# Show database statistics
./bin/dlang_mcp --stats

# Show runtime feature status
./bin/dlang_mcp --feature-status

# Ingest a single package from code.dlang.org
./bin/dlang_mcp --ingest --package=silly

# Ingest all packages from code.dlang.org
./bin/dlang_mcp --ingest

# Ingest with limit and fresh start
./bin/dlang_mcp --ingest --limit=50 --fresh

# Show ingestion progress
./bin/dlang_mcp --ingest-status

# Build vector embeddings
./bin/dlang_mcp --train-embeddings

# Mine usage patterns from indexed data
./bin/dlang_mcp --mine-patterns

# Analyze a D project (standalone, no MCP)
./bin/dlang_mcp --analyze-project=/path/to/project
./bin/dlang_mcp --ddoc-analyze=/path/to/project

# Test search with a query
./bin/dlang_mcp --test-search="hash table lookup"

# Verbose logging (--verbose for info, --vverbose for trace)
./bin/dlang_mcp --verbose

# Set process execution timeout (default: 30s)
./bin/dlang_mcp --timeout=60

# Show help
./bin/dlang_mcp --help

Run MCP Tools Directly (No MCP Client Needed)

Every MCP tool can be invoked directly from the command line. Pass a JSON string of parameters and get the full ToolResult back as JSON on stdout.

# Format D code
./bin/dlang_mcp --dfmt='{"code":"int x=1;"}'

# Static analysis
./bin/dlang_mcp --dscanner='{"code":"void main(){}", "mode":"sloc"}'

# Compile-check inline code
./bin/dlang_mcp --compile-check='{"code":"import std.stdio; void main(){writeln(42);}"}'

# Build a project
./bin/dlang_mcp --build-project='{"project_path":"."}'

# Run project tests
./bin/dlang_mcp --run-tests='{"project_path":".", "verbose":true}'

# Get module outline
./bin/dlang_mcp --module-outline='{"code":"module test; void foo() {}"}'

# Search symbol definitions
./bin/dlang_mcp --ctags-search='{"query":"main", "project_path":"."}'

# Fetch a dub package
./bin/dlang_mcp --fetch-package='{"package_name":"silly"}'

# Analyze coverage (just pass the .lst file)
./bin/dlang_mcp --coverage-analysis=source-app.lst

All 19 tool flags:

Flag	Tool
--dscanner=JSON	Static analysis
--dfmt=JSON	Code formatting
--compile-check=JSON	Compile checking
--coverage-analysis=FILE	Coverage analysis (pass a .lst file directly)
--build-project=JSON	Build project
--run-tests=JSON	Run tests
--run-project=JSON	Run project
--fetch-package=JSON	Fetch package
--upgrade-dependencies=JSON	Upgrade deps
--tool-analyze-project=JSON	Analyze project
--tool-ddoc-analyze=JSON	DDoc analysis
--module-outline=JSON	Module outline
--list-modules=JSON	List modules
--ctags-search=JSON	Symbol search
--search-packages=JSON	Search packages
--search-functions=JSON	Search functions
--search-types=JSON	Search types
--search-examples=JSON	Search examples
--get-imports=JSON	Get imports

--tool-analyze-project and --tool-ddoc-analyze are prefixed with tool- to avoid conflict with the existing --analyze-project and --ddoc-analyze flags (which write to files instead of printing JSON).

Semantic Search Setup (Optional)

The search tools work out of the box with TF-IDF keyword search. For better results, you can optionally enable vector similarity search and/or neural embeddings.

sqlite-vec (Vector Similarity)

Enables vector-based semantic similarity search beyond keyword matching.

Build from source:

cd /tmp
git clone https://github.com/asg017/sqlite-vec
cd sqlite-vec
make loadable
cp dist/vec0.so /path/to/dlang_mcp/data/models/

Or use an environment variable:

export SQLITE_VEC_PATH=/path/to/vec0.so
./bin/dlang_mcp --init-db

Auto-detection paths:

• data/models/vec0.so (Linux) / vec0.dylib (macOS) / vec0.dll (Windows)
• /usr/local/lib/vec0.*
• /usr/lib/vec0.*

Verify with ./bin/dlang_mcp --init-db — should show "Vector search enabled (sqlite-vec)".

ONNX Embeddings (Neural Search)

For semantic embeddings using the all-MiniLM-L6-v2 model:

# Download ONNX model and vocabulary
wget -O data/models/model.onnx \
  https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/resolve/main/onnx/model.onnx
wget -O data/models/vocab.txt \
  https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/raw/main/vocab.txt

# Install ONNX Runtime library
cd /tmp
wget https://github.com/microsoft/onnxruntime/releases/download/v1.18.0/onnxruntime-linux-x64-1.18.0.tgz
tar xzf onnxruntime-linux-x64-1.18.0.tgz
mkdir -p /path/to/dlang_mcp/lib
cp onnxruntime-linux-x64-1.18.0/lib/libonnxruntime.so.1.18.0 /path/to/dlang_mcp/lib/
cd /path/to/dlang_mcp/lib && ln -sf libonnxruntime.so.1.18.0 onnxruntime.so

The binary has an embedded rpath ($ORIGIN/../lib) so it finds the ONNX Runtime library automatically when placed in lib/ next to the bin/ directory.

When the ONNX model and library are available, the server uses neural embeddings for better semantic search. Otherwise, TF-IDF is used as fallback.

Indexing Packages

# Index a single package
./bin/dlang_mcp --ingest --package=silly

# Index all packages (takes a while)
./bin/dlang_mcp --ingest

# Resume interrupted ingestion (automatic)
./bin/dlang_mcp --ingest

# Start fresh
./bin/dlang_mcp --ingest --fresh

# Check ingestion progress
./bin/dlang_mcp --ingest-status

# Mine usage patterns after ingesting
./bin/dlang_mcp --mine-patterns

Troubleshooting

"Vector search disabled"

Make sure sqlite-vec is installed:

ls -la data/models/vec0.so

If missing, build it:

cd /tmp
git clone https://github.com/asg017/sqlite-vec
cd sqlite-vec
make loadable
cp dist/vec0.so /path/to/dlang_mcp/data/models/

"Failed to load sqlite-vec"

Check the extension is compatible with your SQLite version:

sqlite3 --version

The extension requires SQLite 3.40+.

Ingestion fails for a package

Some packages may have unusual structures. Check the error message and try:

# Clear cache and retry
rm -rf data/cache/sources/<package-name>
./bin/dlang_mcp --ingest --package=<package>

License

BOOST — see LICENSE for the full text.