Lightweight MCP server for ContextDigger - enables AI tools to access all 50+ CLI commands
Project description
ContextDigger MCP Server
Lightweight Model Context Protocol (MCP) server for ContextDigger that enables AI tools (Claude Desktop, Cursor, Windsurf, etc.) to access all 50+ ContextDigger CLI commands.
What This Is
This package provides only the MCP server - a lightweight bridge between AI tools and your locally installed ContextDigger CLI.
Architecture:
AI Tool (Claude Desktop)
↓
MCP Protocol
↓
contextdigger-mcp (this package)
↓
subprocess calls
↓
contextdigger CLI (separate installation)
↓
Your .cdg/ data
Benefits
- ✅ Lightweight: Only ~600 lines of code, minimal dependencies
- ✅ Separate installation: Install/update independently from ContextDigger CLI
- ✅ Version flexible: Works with any version of contextdigger CLI
- ✅ Full CLI parity: All 50+ commands available as MCP tools
- ✅ Easy to maintain: No service layer duplication
Installation
Step 1: Install ContextDigger CLI (required)
pip install contextdigger
Step 2: Install MCP Server (this package)
pip install contextdigger-mcp
Step 3: Verify installation
contextdigger --version # Should show CLI version
contextdigger-mcp --help # Should show MCP server is ready
Setup for Claude Desktop
macOS: Edit ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: Edit %APPDATA%\Claude\claude_desktop_config.json
Linux: Edit ~/.config/Claude/claude_desktop_config.json
Add this configuration:
{
"mcpServers": {
"contextdigger": {
"command": "contextdigger-mcp"
}
}
}
If using a virtual environment:
{
"mcpServers": {
"contextdigger": {
"command": "/path/to/venv/bin/contextdigger-mcp"
}
}
}
Restart Claude Desktop to activate.
Available MCP Tools (50+ tools)
Core Navigation (7 tools)
init_project- Initialize ContextDiggerdig_area- Focus on specific arealist_areas- List all areasnavigate_back- Go to previous areanavigate_forward- Go to next areashow_history- Show navigation historyshow_status- Show current session status
Bookmarks (4 tools)
create_bookmark- Save bookmarkgoto_bookmark- Jump to bookmarklist_bookmarks- List all bookmarksdelete_bookmark- Delete bookmark
Context Snapshots (4 tools)
save_context- Save context snapshotload_context- Load context snapshotlist_contexts- List all snapshotsdelete_context- Delete snapshot
Notes & Documentation (3 tools)
add_note- Add note to areashow_notes- View notesgenerate_wiki- Generate wiki docs
Analysis & Intelligence (12 tools)
show_insights- Generate insightssuggest_areas- Get AI suggestionsshow_dependencies- Show dependenciesanalyze_impact- Impact analysisshow_map- Generate codebase mapfind_hotspots- Find code hotspotsfind_gaps- Find coverage gapsanalyze_performance- Performance analysisrun_benchmark- Run benchmarksshow_trends- Historical trend analysis (v2.2.0)show_predictions- Predictive insights (v2.2.0)get_remediation- Automated remediation (v2.2.0)
Search & Query (2 tools)
search_all- Search all areasrun_query- Custom query
Automation (2 tools)
show_automation- Automation suggestionslist_rules- List automation rules
Reports & Export (8 tools)
show_analytics- Work analyticsgenerate_report- Generate reportexport_context- Export contextcreate_backup- Backup .cdg/show_provenance- File provenanceshow_dashboard- Dashboardcheck_health- Health checkshow_stats- Statistics
Team Features (2 tools)
show_team_activity- Team activityshow_test_coverage- Test coverage
Sub-Area Management (2 tools)
split_area- Split large areascreate_subarea- Create sub-area
Budget & Governance (3 tools)
check_budget- Runpolicy checkto verify budget compliancemanage_policy- Manage policy enforcement mode (strict,warning,advisory)show_audit- Show audit trail
Continuation Contracts (3 tools)
continue_work- Resume work sessionpause_work- Pause worklist_contracts- List all sessions
LLM Integration (1 tool)
manage_llm- Manage LLM integration
Example Usage
Once configured in Claude Desktop, you can use natural language:
User: "Show me all focus areas in this project"
Claude: Uses list_areas tool
User: "Dig into the API area"
Claude: Uses dig_area tool with area_id="api"
User: "What insights do you have?"
Claude: Uses show_insights tool
User: "Analyze trends over time"
Claude: Uses show_trends tool
Troubleshooting
"contextdigger CLI not found"
Solution:
pip install contextdigger
contextdigger --version # Verify it works
MCP server not showing in Claude Desktop
- Check JSON syntax in config file
- Use full path to
contextdigger-mcpif in venv - Completely quit and restart Claude Desktop
- Check Claude Desktop logs (Help → Show Logs)
Command timeout
Some commands may take longer than 60 seconds. This is a safety limit. You can:
- Use the CLI directly for long-running commands
- Split large areas into smaller sub-areas
- Adjust budget limits to reduce context size
How It Works
- AI tool sends MCP request (JSON-RPC over stdin)
- MCP server parses request and identifies the tool
- Server calls contextdigger CLI via subprocess
- CLI executes command and returns output
- Server formats response and sends back to AI (via stdout)
All processing is local - no external services involved.
Differences from Main Package
contextdigger package (main):
- Full CLI with 50+ commands
- Service layer (manager, insights, budget, etc.)
- Direct Python imports
- Faster execution
- Entry point:
contextdigger
contextdigger-mcp package (this):
- Only MCP server
- Calls CLI via subprocess
- Lightweight (~600 lines)
- Separate installation
- Entry point:
contextdigger-mcp
Requirements
- Python 3.11+
- ContextDigger CLI (
pip install contextdigger) - AI tool with MCP support (Claude Desktop, Cursor, etc.)
License
MIT License - See LICENSE file
Links
Made with ⛏️ by the ContextDigger team
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