Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yoanbernabeu/grepai-skills --skill grepai-mcp-cursorgit clone --depth 1 https://github.com/yoanbernabeu/grepai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-mcp-cursor)<a href="https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-mcp-cursor"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-mcp-cursor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yoanbernabeu/grepai-skills/grepai-mcp-cursor"><img src="https://agentmods.dev/badge/skills/yoanbernabeu/grepai-skills/grepai-mcp-cursor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.01604 |
| Opus 5 | $0.00015 | $0.00802 |
| Sonnet 5 | $0.00006 | $0.00321 |
| Haiku 4.5 | $0.00003 | $0.00160 |
Grade B, and why
grepai-mcp-cursor scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads MCP configurationmediumAgent snooping
mcp.json carries server URLs and auth tokens; reading it lets a mod discover and abuse other integrations.
1. **Version control:** Add `.cursor/mcp.json` to git (without secrets) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. Check Ollama: `curl http://localhost:11434/api/tags` How it starts
The opening of the file, as written. The whole thing — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GrepAI MCP Integration with Cursor
This skill covers integrating GrepAI with Cursor IDE using the Model Context Protocol (MCP).
When to Use This Skill
- Setting up GrepAI in Cursor
- Enabling semantic search for Cursor AI
- Configuring MCP for Cursor
- Troubleshooting Cursor integration
What is Cursor?
Cursor is an AI-powered IDE that supports MCP for external tools. GrepAI integration gives Cursor's AI:
- Semantic code search beyond simple text matching
- Call graph analysis for understanding dependencies
- Index-based code navigation
Prerequisites
- GrepAI installed
- Ollama running (or other embedding provider)
- Project indexed (
grepai watch) - Cursor IDE installed
Configuration
Step 1: Create MCP Config File
Create .cursor/mcp.json in your project root:
{
"mcpServers": {
"grepai": {
"command": "grepai",
"args": ["mcp-serve"]
}
}
}
Step 2: Restart Cursor
Close and reopen Cursor for the config to take effect.
Step 3: Verify
Ask Cursor's AI:
"Search the codebase for authentication"
Cursor should use the grepai_search tool.
Global Configuration
For GrepAI in all Cursor projects, use global config:
Location
- macOS:
~/.cursor/mcp.json - Linux:
~/.cursor/mcp.json - Windows:
%APPDATA%\Cursor\mcp.json
Content
{
"mcpServers": {
"grepai": {
"command": "grepai",
"args": ["mcp-serve"]
}
}
}
Per-Project Configuration
For project-specific settings:
{
"mcpServers": {
"grepai": {
"command": "grepai",
"args": ["mcp-serve"],
"cwd": "/absolute/path/to/project"
}
}
}
Available Tools
Once configured, Cursor has access to:
| Tool | Description |
|---|---|
grepai_search |
Semantic code search |
grepai_trace_callers |
Find function callers |
grepai_trace_callees |
Find function callees |
grepai_trace_graph |
Build call graphs |
grepai_index_status |
Check index health |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 311 lines · 29 tokens per session scan B dfed5c71e443
grepai-mcp-cursor is a skill published in the GitHub repository yoanbernabeu/grepai-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 29 tokens to every session and 1,604 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 2 findings (reads mcp configuration, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
codebase-search
Semantic code and documentation search by meaning. Use codebasepeek to find WHERE code is (saves tokens), codebasesearch to see actual code. For exact identifiers, use grep instead. Search local codebase before using websearch for code/library/API/example questions.
qdrant-advisor
Diagnose, troubleshoot, and advise on any Qdrant deployment by loading the latest official Qdrant skills live from skills.qdrant.tech. Use this whenever someone raises a Qdrant problem or question — slow or degraded search, high or growing memory / OOM crashes, optimizer stuck or slow, indexing slowness, scaling and…
qdrant-search-quality-diagnosis
Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact', 'which embedding model', 'quality dropped after quantization', 'how to measure retrieval quality', 'build a golden…
qdrant-monitoring-debugging
Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.
codebase-search
Preferred local codebase-understanding workflow for Pi and Codex. Start with codebasecontext before shell search or broad reads, then use specialized semantic and graph tools.
cocosearch-debugging
Use when debugging an error, unexpected behavior, or tracing how code flows through a system. Guides root cause analysis using CocoSearch semantic and symbol search.