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Retrieve grounded resume evidence for a job description using BM25 + evidence reranking
About
Retrieve grounded resume evidence for a job description using BM25 + evidence reranking
Security Report
This is a collection of practical LLM applications and MCP servers with clean, well-structured code. The servers implement appropriate authentication via environment variables and have no malicious patterns or dangerous operations. Minor code quality observations (broad exception handling, lack of input sanitization in some areas) are present but do not pose material security risks. Permissions align with the stated purpose of the applications. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue (1 critical, 0 high severity).
8 files analyzed · 11 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
Unverified package source
We couldn't verify that the installable package matches the reviewed source code. Proceed with caution.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-nimish14-resume-evidence-mcp": {
"args": [
"-y",
"freelance-ops-mcp"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Practical LLM Apps
Clone-and-run AI agents, RAG apps, and MCP servers.
Hand-built examples you can customize and ship — not slide-deck demos.
Works with OpenAI, and several apps run fully local with no API key.
Run one now
Invoice Follow-up Agent
git clone https://github.com/nimish14/practical-llm-apps.git
cd practical-llm-apps/starter_ai_agents/invoice_followup_agent
pip install -r requirements.txt
cp .env.example .env # add OPENAI_API_KEY
streamlit run app.py
Chat with PDF
cd practical-llm-apps/starter_ai_agents/chat_with_pdf
pip install -r requirements.txt
cp .env.example .env # add OPENAI_API_KEY
streamlit run app.py
Resume Evidence RAG (no API key)
cd practical-llm-apps/rag_apps/resume_evidence_rag
pip install -r requirements.txt
streamlit run app.py
Freelance Ops MCP (Cursor / Claude)
cd practical-llm-apps/mcp_servers/freelance-ops-mcp
npm install
npm run build
npx -y @modelcontextprotocol/inspector node dist/index.js
Add to Cursor MCP settings:
{
"mcpServers": {
"freelance-ops": {
"command": "npx",
"args": ["-y", "freelance-ops-mcp"]
}
}
}
(After npm publish — until then, point args at node + local dist/index.js.)
Browse templates
Starter AI Agents
| App | Description |
|---|---|
| Invoice Follow-up Agent | Draft polite → firm invoice reminders with tone control and overdue context |
| Chat with PDF | Ask questions about an uploaded PDF with page citations |
RAG Apps
| App | Description |
|---|---|
| Resume Evidence RAG | Hybrid MiniLM + BM25 retrieval that returns grounded resume facts for a job description |
MCP Servers
| Server | Description |
|---|---|
| freelance-ops-mcp | Tools for overdue status, tone suggestion, and invoice reminder drafts |
| resume-evidence-mcp | BM25 resume evidence retrieval tools for coding agents |
Project goals
- Every app: clone → install → run in under 2 minutes
- Clear README with problem, pipeline, and limits
- MCP servers packaged for npm + MCP Registry
- Prefer small, focused tools over mega-frameworks
License
MIT — fork it, ship it, sell it.
Reviews
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