BigBugAI MCP Server
Uses FastAPI framework to provide HTTP/SSE transport for remote MCP client access, enabling web-based interaction with BigBugAI tools
Utilizes Pydantic for typed schemas and data validation for tool input/output handling
Uses pytest framework for unit testing the MCP server functionality
Built as a Python-based MCP server providing BigBugAI cryptocurrency analysis tools
Employs Ruff for code linting and formatting to maintain code quality
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@BigBugAI MCP Servershow me the top 5 trending tokens"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
BigBugAI MCP (Python + FastMCP)
Production-ready MCP server exposing BigBugAI tools with stdio transport for local MCP clients (Claude Desktop, Cursor) and optional HTTP/SSE transport (FastAPI + uvicorn) for remote access.
Auth via API key (env var)
Per-key rate limiting (moving window; configurable via env)
Typed Pydantic schemas for tool I/O
Clean error handling and JSON-stable outputs
Tests, ruff, and mypy configuration
Tools
get_trending_tokens(limit: int = 10) -> list[dict]GET
${BTUNIFIED_API}/api/tokens/newly-ingestedby defaultFalls back to
${BTUNIFIED_API}/v1/trending/tokensand a few other candidates if 404Override primary path with
BTUNIFIED_TRENDING_PATHNormalizes
{items: [...]} -> [...]
token_analysis_by_contract(chain: str, address: str) -> dictGET
${BTUNIFIED_API}/api/token-intel/{chain}/{address}/report
Requirements
Python 3.11+
Packages:
mcp[cli],httpx,pydantic,fastapi,uvicorn,limits,pytest,ruff,mypy
Environment variables
BIGBUGAI_MCP_API_KEY(required)BIGBUGAI_API_KEY/BIGBUGAI_API_TOKEN(optional; used for upstream HTTP calls if set. If not set, HTTP calls will fall back toBIGBUGAI_MCP_API_KEY.)BTUNIFIED_API(default:https://api.bigbug.ai)MCP_RATE_LIMIT(default:60/hour, rate string perlimits)
Install
Using uv (recommended):
Unix/macOS
uv venv
source .venv/bin/activate
uv pip install -e .[dev]Windows PowerShell
uv venv
.venv\Scripts\Activate.ps1
uv pip install -e .[dev]Alternatively, you can explicitly add packages (will update pyproject as needed):
uv add "mcp[cli]" httpx pydantic fastapi uvicorn limits pytest ruff mypyRun (STDIO)
export BIGBUGAI_MCP_API_KEY="your-secret"
export BTUNIFIED_API="https://api.bigbug.ai"
uv run -m bigbugai_mcp.server_stdioWindows PowerShell:
$env:BIGBUGAI_MCP_API_KEY="your-secret"
$env:BTUNIFIED_API="https://api.bigbug.ai"
uv run -m bigbugai_mcp.server_stdioThis mode is intended for local MCP clients (e.g., Claude Desktop, Cursor).
Note: Tools no longer require api_key in the payload. The server reads the API key
from the environment (BIGBUGAI_MCP_API_KEY) and applies rate limiting based on it.
Claude Desktop config
Create claude_desktop_config.json:
{
"mcpServers": {
"bigbugai": {
"command": "uv",
"args": ["-m", "bigbugai_mcp.server_stdio"],
"env": {
"BIGBUGAI_MCP_API_KEY": "your-secret",
"BTUNIFIED_API": "https://api.bigbug.ai",
"MCP_RATE_LIMIT": "60/hour"
}
}
}
}Run (HTTP)
uv run -m bigbugai_mcp.server_http
# server on :8000
curl -s http://localhost:8000/healthzExpected output:
okMCP HTTP/SSE endpoints are mounted under /mcp. Depending on your FastMCP version, an SSE stream may be available at /mcp/sse.
Example cURL (SSE; may require -N to keep the connection open and is primarily for debugging):
curl -N http://localhost:8000/mcp/sseNote: MCP over HTTP/SSE is designed for compatible clients; manual cURL interaction is limited.
Smoke scripts
Quick sanity checks for the tools (require an API key in env):
Trending
# uses BIGBUGAI_API_KEY/BIGBUGAI_API_TOKEN/BIGBUGAI_MCP_API_KEY from env uv run python scripts/smoke_trending.py -l 5Token analysis
# requires BIGBUGAI_MCP_API_KEY in env; optionally set BB_CHAIN/BB_ADDRESS $env:BIGBUGAI_MCP_API_KEY="your-secret" # PowerShell uv run python scripts/smoke_token_analysis.py
Testing and Quality
# Run unit tests
uv run pytest -q
# Lint
uv run ruff check .
# Type check
uv run mypy srcProject layout
bigbugai-mcp/
.github/workflows/ci.yml
CODE_OF_CONDUCT.md
CONTRIBUTING.md
LICENSE
README.md
SECURITY.md
pyproject.toml
scripts/list_tools.py
scripts/smoke_token_analysis.py
scripts/smoke_trending.py
src/bigbugai_mcp/__init__.py
src/bigbugai_mcp/auth.py
src/bigbugai_mcp/models.py
src/bigbugai_mcp/server_http.py
src/bigbugai_mcp/server_stdio.py
src/bigbugai_mcp/tools.py
tests/test_tools.pySecurity
Rotate API keys regularly
Keep HTTP mode behind OAuth/reverse proxy if exposed publicly
Rate limits are per API key in a moving window strategy
See SECURITY.md for reporting vulnerabilities.
Extending
Add more tools for BigBugAI endpoints (portfolio manager, investment suggester, etc.).
Add new Pydantic request/response models in
src/bigbugai_mcp/models.pyAdd the tool function in
src/bigbugai_mcp/tools.pyDecorate with
@guardedand register inregister_tools()Write tests in
tests/
Contributing
Please see CONTRIBUTING.md for guidelines.
Code of Conduct
This project follows the Contributor Covenant.
License
MIT — see LICENSE.
This server cannot be installed
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/bigbugAi/bigbugai-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server