grepai-mcp-claude▌
yoanbernabeu/grepai-skills · updated Apr 8, 2026
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This skill covers integrating GrepAI with Claude Code using the Model Context Protocol (MCP).
GrepAI MCP Integration with Claude Code
This skill covers integrating GrepAI with Claude Code using the Model Context Protocol (MCP).
When to Use This Skill
- Setting up GrepAI in Claude Code
- Enabling semantic search for AI coding assistant
- Configuring MCP server for Claude
- Troubleshooting Claude Code integration
What is MCP?
Model Context Protocol (MCP) allows AI assistants to use external tools. GrepAI provides an MCP server that gives Claude Code:
- Semantic code search
- Call graph analysis
- Index status monitoring
Prerequisites
- GrepAI installed
- Ollama running (or other embedding provider)
- Project indexed (
grepai watch) - Claude Code installed
Quick Setup
One command to add GrepAI to Claude Code:
claude mcp add grepai -- grepai mcp-serve
That's it! Claude Code can now use GrepAI tools.
Manual Configuration
If you prefer manual setup, add to Claude Code's MCP config:
Location
- macOS/Linux:
~/.claude/mcp.json - Windows:
%APPDATA%\Claude\mcp.json
Configuration
{
"mcpServers": {
"grepai": {
"command": "grepai",
"args": ["mcp-serve"]
}
}
}
With Working Directory
If you want GrepAI to always use a specific project:
{
"mcpServers": {
"grepai": {
"command": "grepai",
"args": ["mcp-serve"],
"cwd": "/path/to/your/project"
}
}
}
Verifying Installation
Check MCP Server
# Start MCP server manually to test
grepai mcp-serve
You should see:
GrepAI MCP Server started
Listening for requests...
In Claude Code
Ask Claude:
"Search the codebase for authentication code"
Claude should use the grepai_search tool.
Available Tools
Once connected, Claude Code has access to these tools:
| Tool | Description | Parameters |
|---|---|---|
grepai_search |
Semantic code search | query (required), limit, compact |
grepai_trace_callers |
Find function callers | symbol (required), compact |
grepai_trace_callees |
Find function callees | symbol (required), compact |
grepai_trace_graph |
Build call graph | symbol (required), depth |
grepai_index_status |
Check index health | verbose (optional) |
Tool Usage Examples
Semantic Search
Claude request:
"Find code related to user authentication"
Claude uses:
{
"tool": "grepai_search",
"parameters": {
"query": "user authentication",
"limit": 5,
"compact": true
}
}
Trace Analysis
Claude request:
"What functions call the Login function?"
Claude uses:
{
"tool": "grepai_trace_callers",
"parameters": {
"symbol": "Login",
"compact": true
}
}
Index Status
Claude request:
"Is the code index up to date?"
Claude uses:
{
"tool": "grepai_index_status",
"parameters": {
"verbose": true
}
}
Compact Mode
By default, MCP tools return compact JSON to minimize tokens:
{
"q": "authentication",
"r": [
{"s": 0.92, "f": "src/auth/middleware.go", "l": "15-45"},
{"s": 0.85, "f": "src/auth/jwt.go", "l": "23-55"}
],
"t": 2
}
This reduces token usage by ~80% compared to full content.
Working Directory
The MCP server uses the current working directory. Ensure:
- GrepAI is initialized in your project
- Index exists (run
grepai watchfirst) - Start Claude Code from your project directory
Option 1: Start Claude from Project Directory
cd /path/to/your/project
claude # Claude Code now uses this directory
Option 2: Configure CWD in MCP Config
{
"mcpServers": {
"grepai": {
"command": "grepai",
"args": ["mcp-serve"],
"cwd": "/path/to/your/project"
}
}
}
Multiple Projects
For multiple projects, you can:
Option 1: Multiple MCP Servers
{
"mcpServers": {
"grepai-frontend": {
"command": "grepai",
"args": ["mcp-serve"],
"cwd": "/path/to/frontend"
},
"grepai-backend": {
"command": "grepai",
"args": ["mcp-serve"],
"cwd": "/path/to/backend"
}
}
}
Option 2: Use Workspaces
grepai workspace create my-workspace
grepai workspace add my-workspace /path/to/frontend
grepai workspace add my-workspace /path/to/backend
{
"mcpServers": {
"grepai": {
"command": "grepai",
"args": ["mcp-serve", "--workspace", "my-workspace"]
}
}
}
Troubleshooting
Tool Not Available
❌ Problem: Claude doesn't see GrepAI tools
✅ Solutions:
- Restart Claude Code after config changes
- Check MCP config syntax (valid JSON)
- Verify
grepaiis in PATH - Test:
grepai mcp-servemanually
Search Returns No Results
❌ Problem: Searches return empty
✅ Solutions:
- Ensure
grepai watchhas run - Check working directory has
.grepai/ - Verify index exists:
grepai status
Connection Refused
❌ Problem: MCP server won't start
✅ Solutions:
- Check Ollama is running:
curl http://localhost:11434/api/tags - Verify config:
cat .grepai/config.yaml - Run
grepai mcp-servemanually to see errors
Wrong Project Indexed
❌ Problem: Results from wrong codebase
✅ Solutions:
- Check
cwdin MCP config - Start Claude from correct directory
- Verify with
grepai_index_statustool
Best Practices
- Keep index updated: Run
grepai watch --background - Use compact mode: Reduces token usage
- Set working directory: Explicit
cwdin config - Check status first: Use
grepai_index_status - Restart after config: Claude needs restart for MCP changes
Removing Integration
To remove GrepAI from Claude Code:
claude mcp remove grepai
Or manually edit ~/.claude/mcp.json and remove the grepai entry.
Output Format
Successful MCP setup:
✅ GrepAI MCP Integration Configured
Claude Code: ~/.claude/mcp.json
Server: grepai mcp-serve
Status: Connected
Available tools:
- grepai_search (semantic code search)
- grepai_trace_callers (find callers)
- grepai_trace_callees (find callees)
- grepai_trace_graph (call graphs)
- grepai_index_status (index health)
Claude can now search your code semantically!
How to use grepai-mcp-claude on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add grepai-mcp-claude
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches grepai-mcp-claude from GitHub repository yoanbernabeu/grepai-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate grepai-mcp-claude. Access the skill through slash commands (e.g., /grepai-mcp-claude) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★37 reviews- ★★★★★Anaya Dixit· Dec 28, 2024
Registry listing for grepai-mcp-claude matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Chaitanya Patil· Dec 12, 2024
grepai-mcp-claude has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Liam Nasser· Dec 12, 2024
Useful defaults in grepai-mcp-claude — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Layla Thompson· Dec 8, 2024
Keeps context tight: grepai-mcp-claude is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Henry Bhatia· Nov 27, 2024
grepai-mcp-claude is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Advait Malhotra· Nov 19, 2024
grepai-mcp-claude fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Arjun Sharma· Nov 7, 2024
I recommend grepai-mcp-claude for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Piyush G· Nov 3, 2024
Solid pick for teams standardizing on skills: grepai-mcp-claude is focused, and the summary matches what you get after install.
- ★★★★★Noor Khanna· Nov 3, 2024
We added grepai-mcp-claude from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Arya Srinivasan· Oct 26, 2024
grepai-mcp-claude reduced setup friction for our internal harness; good balance of opinion and flexibility.
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