MarketIntel MCP Server
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
MarketIntel MCP Server (Azure Container Apps)
Cloud-hosted MCP server exposing market-research tools over SSE, per
MarketIntel_MCP_Server_Azure_Spec.md. Developers connect from VS Code
(Copilot Chat Agent mode) to a shared Azure HTTPS endpoint — no local server.
Layout
MCPServer/
├── server.py # Entrypoint (spec §7.3): binds 0.0.0.0:8000, SSE
├── market_intel/
│ ├── config.py # Env-driven settings; secrets via env only (§9)
│ ├── providers.py # SearchProvider seam: Tavily (prod) / Fake (offline)
│ ├── tools.py # 5 tools + resource + prompt logic (§6, §10)
│ └── mcp_app.py # FastMCP wiring (lazy import)
├── tests/test_tools.py # 17 offline unit tests (§11)
├── Dockerfile # python:3.12-slim + uv (§7.2)
├── infra/deploy.sh # az containerapp up + scale rules (§7.4, §8)
├── .vscode/mcp.json # VS Code MCP client config (§7.5)
└── .env.exampleRelated MCP server: Deep Research MCP
Run locally (offline, no key)
python -m pytest -q # 17 passing
SEARCH_PROVIDER=fake python server.py # serves SSE on :8000 (needs fastmcp)Run with real Tavily
pip install fastmcp tavily-python uvicorn
export TAVILY_API_KEY=tvly-... # SEARCH_PROVIDER defaults to tavily
python server.pyDeploy to Azure
export TAVILY_KEY=tvly-...
bash infra/deploy.sh # prints the *.azurecontainerapps.io FQDNThen set the /sse URL in .vscode/mcp.json.
Design note
The Tavily dependency is behind a SearchProvider adapter (spec-driven offline
seam): FakeSearchProvider makes the full tool pipeline + tests run with zero
network and no API key; TavilyProvider (lazy-imported SDK) is selected by
SEARCH_PROVIDER=tavily for production. Same contract, one config flag.
Tool Schema Changelog
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This server cannot be deployed
Maintenance
Related MCP Connectors
Live context for your agent: competitors, mentions and markets, from public data.
Investment research superagent: podcasts, SEC filings, and no-code research pipelines.
Market knowledge layer for AI agents: competitors, opinions and regulations shaping your market.
Google Trends, Google News, Hacker News, Substack posts and podcasts for research and monitoring.
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