Next-Generation MCP Server
Enables sandboxed file operations via MCP tools, resources, and prompts, with a Claude CLI client and Groq-powered web UI for file CRUD, search, code review, and documentation generation.
README
<h1 align="center">๐๏ธ Next-Generation MCP Server</h1>
<p align="center"> A modular <b>FastMCP</b> file-operations server, a faithful <b>Claude</b> CLI client, and a <b>Groq-powered</b> ChatGPT-style web UI. </p>
<p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue" alt="Python 3.10+" /> <img src="https://img.shields.io/badge/FastMCP-2.12-purple" alt="FastMCP" /> <img src="https://img.shields.io/badge/UI-Chainlit-ff4b6e" alt="Chainlit" /> <img src="https://img.shields.io/badge/MCP-STDIO-green" alt="MCP STDIO" /> </p>
A sandboxed file-operations MCP server that showcases the advanced Context
features โ logging, progress reporting, and user elicitation โ with
two ways to drive it: a Claude CLI (client.py) and a Groq web chat (app.py).
Capabilities
๐ ๏ธ Tools (model-controlled โ the agent calls them):
| Tool | Description |
|---|---|
write_file(file_path, content) |
Create/overwrite a file (with progress reporting) |
read_file(file_path) |
Read a file's content |
append_to_file(file_path, content) |
Append to a file |
delete_file(file_path) |
Delete a file |
move_file(source, destination) |
Move / rename |
copy_file(source, destination) |
Copy a file |
make_directory(dir_path) |
Create a directory |
search_files(query, extension) |
Search file contents across the project |
file_info(file_path) |
File/dir metadata |
๐ Resources (app-controlled): file:///{file_name} (read file) ยท dir://. (list dir) ยท stats://project (project statistics)
๐ฌ Prompts (user-controlled): code_review ยท documentation_generator (elicitation) ยท generate_tests ยท explain_code
Project structure
next-generation-mcp-server/
โโโ fileops/ # modular MCP server package
โ โโโ config.py # BASE_DIR, server name/instructions, ignore list
โ โโโ paths.py # get_path() path-traversal guard
โ โโโ schemas.py # Pydantic models (elicitation)
โ โโโ server.py # builds `mcp`, registers tools/resources/prompts
โ โโโ tools.py # @mcp.tool definitions
โ โโโ resources.py # @mcp.resource definitions
โ โโโ prompts.py # @mcp.prompt definitions
โโโ server.py # entry point โ python server.py
โโโ client.py # Claude CLI client (Anthropic)
โโโ app.py # Groq chat UI (Chainlit)
โโโ chainlit.md
โโโ tests/test_server.py # smoke test of all capabilities
โโโ pyproject.toml ยท requirements.txt ยท .env.example ยท .gitignore ยท README.md
Setup
cd next-generation-mcp-server
python -m venv .venv
.\.venv\Scripts\Activate.ps1 # Windows (macOS/Linux: source .venv/bin/activate)
pip install -r requirements.txt
Add a key to .env (Copy-Item .env.example .env):
GROQ_API_KEYโ free at console.groq.com, used by the web UI (app.py).ANTHROPIC_API_KEYโ used by the CLI (client.py).
Run
Web chat UI (Groq):
chainlit run app.py -w # โ http://localhost:8200
Chat to use the file tools; slash commands for the rest:
/dir ยท /read <f> ยท /stats ยท /tools ยท /review <f> ยท /tests <f> ยท /explain <f> ยท /docs ยท /help.
You can also attach a file and say "review this file".
Claude CLI (Anthropic):
python client.py server.py
Run the server directly / tests:
python server.py
python tests\test_server.py # or: python -m pytest
How it works
- The server runs over STDIO; the client/UI spawn it as a subprocess.
- Tools are model-controlled (the agent calls them in its loop).
- Resources are app-controlled (
/dir,/read,/stats). - Prompts are user-controlled (
/review,/tests,/explain,/docs).
Based on the IBM Skills Network "Enhanced MCP Server" lab, refactored into a modular package and extended with more tools, resources, prompts, and a Groq UI.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.