mgrep is a semantic search tool that enables natural language queries across code, text, PDFs, and images. It is particularly effective for exploring larger or complex codebases where traditional pattern matching falls short.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmgrep-code-searchExecute the skills CLI command in your project's root directory to begin installation:
Fetches mgrep-code-search from intellectronica/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate mgrep-code-search. Access via /mgrep-code-search in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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mgrep is a semantic search tool that enables natural language queries across code, text, PDFs, and images. It is particularly effective for exploring larger or complex codebases where traditional pattern matching falls short.
Use mgrep when:
Use traditional grep/ripgrep when:
Before searching, start the watcher to index the repository:
bunx @mixedbread/mgrep watch
The watch command indexes the repository and maintains synchronisation with file changes. It respects .gitignore and .mgrepignore patterns.
bunx @mixedbread/mgrep "your natural language query" [path]
bunx @mixedbread/mgrep "where is authentication configured?"
bunx @mixedbread/mgrep "how do we handle errors in API calls?" src/
bunx @mixedbread/mgrep "database connection setup" src/lib
| Option | Description |
|---|---|
-m <count> |
Maximum results (default: 10) |
-c, --content |
Display full result content |
-a, --answer |
Generate AI-powered synthesis of results |
-s, --sync |
Update index before searching |
--no-rerank |
Disable relevance optimisation |
# Get more results
bunx @mixedbread/mgrep -m 25 "user authentication flow"
# Show full content of matches
bunx @mixedbread/mgrep -c "error handling patterns"
# Get an AI-synthesised answer
bunx @mixedbread/mgrep -a "how does the caching layer work?"
# Sync index before searching
bunx @mixedbread/mgrep -s "payment processing" src/services
Start watcher (once per session or when files change significantly):
bunx @mixedbread/mgrep watch
Search semantically:
bunx @mixedbread/mgrep "what you're looking for" [optional/path]
Refine as needed using path constraints or options:
bunx @mixedbread/mgrep -m 20 -c "refined query" src/specific/directory
Configure defaults via environment variables:
| Variable | Purpose |
|---|---|
MGREP_MAX_COUNT |
Default result limit |
MGREP_CONTENT |
Enable content display (1/true) |
MGREP_ANSWER |
Enable AI synthesis (1/true) |
MGREP_SYNC |
Pre-search sync (1/true) |
bunx @mixedbread/mgrep to run commands (not npm/npx or direct installation)bunx @mixedbread/mgrep watch before searching to ensure the index is current.gitignore patterns automatically.mgrepignore for additional exclusionsMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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cursor/plugins
I recommend mgrep-code-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
mgrep-code-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in mgrep-code-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added mgrep-code-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added mgrep-code-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: mgrep-code-search is focused, and the summary matches what you get after install.
I recommend mgrep-code-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
mgrep-code-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
mgrep-code-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
mgrep-code-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
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