mcp-trendpulse

TrendPulse is a Python Model Context Protocol (MCP) server for researching current news and search-interest trends. It combines Google News discovery and article extraction with Google Trends analysis so MCP clients can inspect what is trending, compare keyword momentum, explore related demand, and add current-news context to research workflows.

The project currently ships as a community/self-hosted MCP server. A separate hosted TrendPulse by DigestSEO integration is being developed for remote MCP clients such as ChatGPT and Codex. The hosted layer will use a smaller, goal-oriented public tool surface while the community server keeps the full low-level research toolkit available to developers.

Project status: the local/community server is usable today. The DigestSEO-hosted MCP and public OpenAI plugin are not released yet and should not be treated as available endpoints.

What TrendPulse can do

News research

• Search Google News by keyword, location, topic, or publisher domain.
• Retrieve top news stories.
• Resolve Google News links and extract article content.
• Fall back from normal HTTP retrieval to Playwright/Chromium for difficult pages.
• Optionally summarize article text with MCP client sampling, with local NLP as a fallback.

Trend research

• Retrieve current trending terms for a geographic market.
• Pull Google Trends interest-over-time data for one or more keywords.
• Calculate keyword growth over custom windows such as 3M or 1Y.
• Rank live trends by volume or growth.
• Inspect interest by country, region, city, or DMA where supported.
• Explore related queries, related topics, suggestions, and category IDs.
• Compare Google Search, YouTube Search, News Search, Image Search, and Google Shopping trend properties where supported by the underlying provider.

Community and hosted architecture

TrendPulse is being developed with two deliberate surfaces:

The community server remains useful independently. The hosted edition will reuse the same core trend-research concepts while adding the deployment, reliability, authentication, observability, and product integration needed for a managed service.

The planned public tool surface is intentionally higher level than the community API and is expected to center on goals such as:

• discover_trends
• analyze_keyword_trend
• compare_keyword_trends
• discover_related_demand
• get_trend_context
• find_seo_opportunities

These names describe the planned hosted/plugin interface; they are not current community MCP tool names yet.

Installation

Run directly from GitHub with uvx (recommended)

The package is not yet published to PyPI, so the most direct installation path is:

uvx --from git+https://github.com/AKzar1el/mcp-trendpulse.git mcp-trendpulse

After a PyPI release exists, the shorter form will be:

uvx mcp-trendpulse

Install with pip from a checkout

git clone https://github.com/AKzar1el/mcp-trendpulse.git
cd mcp-trendpulse
python -m pip install .
python -m mcp_trendpulse

Browser fallback

News/article tools can fall back to Playwright when ordinary retrieval cannot extract a usable article. Installing the Python playwright package does not install Chromium automatically.

For local use:

playwright install chromium

For Linux environments that also require browser system dependencies:

playwright install --with-deps chromium

Trend-only operations do not inherently require Chromium.

Client configuration

Claude Desktop

Using uvx directly from GitHub:

{
  "mcpServers": {
    "mcp-trendpulse": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/AKzar1el/mcp-trendpulse.git",
        "mcp-trendpulse"
      ]
    }
  }
}

VS Code

{
  "mcp": {
    "servers": {
      "mcp-trendpulse": {
        "command": "uvx",
        "args": [
          "--from",
          "git+https://github.com/AKzar1el/mcp-trendpulse.git",
          "mcp-trendpulse"
        ]
      }
    }
  }
}

Cursor

Cursor supports global and project MCP configuration. Add the server to the relevant mcp.json configuration:

{
  "mcpServers": {
    "mcp-trendpulse": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/AKzar1el/mcp-trendpulse.git",
        "mcp-trendpulse"
      ]
    }
  }
}

ChatGPT and other cloud MCP clients

The repository now includes a dedicated stateless Streamable HTTP ASGI entry point at mcp_trendpulse.asgi:app. This is separate from the Community stdio entry point, which remains unchanged.

For controlled local/private testing you can run the ASGI app with Uvicorn or use the provided container. See deploy/README.md for the hardened container, Host/Origin allowlists, Chromium sandbox requirements, health/readiness endpoints, and reverse-proxy notes.

The DigestSEO-hosted endpoint and public OpenAI plugin are still not released. The remote transport currently has no temporary public authentication layer, so do not expose it directly to the open internet before the planned DigestSEO identity integration.

Configuration

TrendPulse loads environment variables from the process environment and from a local .env file when present.

Useful variables include:

HTTP_PROXY=http://your-proxy-address:port
HTTPS_PROXY=http://your-proxy-address:port
GOOGLE_TRENDS_DELAY=2.0

GOOGLE_TRENDS_DELAY controls the request delay used by the current Trends provider. Proxy variables can be useful when the upstream service rate-limits or blocks a particular network.

Remote deployments also support TRENDPULSE_HTTP_PATH, TRENDPULSE_HTTP_ALLOWED_HOSTS, TRENDPULSE_HTTP_ALLOWED_ORIGINS, and TRENDPULSE_BROWSER_SANDBOX. The container enables Chromium sandboxing explicitly; local Community runs retain the Playwright-compatible default unless you opt in.

Do not commit secrets, private proxy credentials, or machine-specific .env files.

MCP tools

The community MCP server currently exposes 16 tools.

News tools

Trend tools

Example: explicit trend window

get_trends accepts an explicit timeframe. Supplying one is preferable when you need reproducible comparisons.

{
  "keyword": ["technical SEO audit", "AI SEO audit"],
  "geo": "US",
  "source": "google search",
  "timeframe": "today 12-m",
  "cat": 0
}

Supported provider ranges include standard windows such as today 12-m and today 5-y, relative windows such as today 90-d, all, and exact date ranges such as 2021-01-01 2026-01-01.

Google Trends values are normalized interest scores. Do not interpret a 0-100 interest series as absolute search volume.

CLI

The separate Click CLI exposes a smaller news-oriented command set than the MCP server:

uv run mcp-trendpulse-cli --help

Current CLI commands:

keyword
location
top
topic
trending

The CLI and MCP surfaces are intentionally documented separately because they do not expose the same command set.

Development

Install the project with its development dependencies using your preferred Python environment, then run the unit suite:

python -m pytest

The default pytest configuration excludes live integration tests.

Run live provider tests explicitly with:

python -m pytest tests/integration -m integration

Browser-marked integration tests require Playwright Chromium to be installed.

Run Ruff checks with:

ruff check .

MCP Inspector

Run the published-from-GitHub server through the MCP Inspector:

npx @modelcontextprotocol/inspector uvx --from git+https://github.com/AKzar1el/mcp-trendpulse.git mcp-trendpulse

For a local checkout:

npx @modelcontextprotocol/inspector uv run mcp-trendpulse

Packaging

A GitHub Actions workflow is already present for building and publishing Python distributions through PyPI Trusted Publishing when a GitHub release is published. Until the first package release exists, use the GitHub uvx --from ... command shown above.

Security notes

Article retrieval is an outbound network feature and is treated as untrusted input. The implementation validates HTTP(S) targets, rejects private and non-routable destinations, checks redirect targets, enforces response-size limits, and applies browser-route validation when Playwright is used.

If you deploy TrendPulse remotely, retain these controls and add deployment-level rate limiting, request timeouts, observability, and resource limits rather than relying only on application defaults.

Roadmap

Current production-readiness work is focused on:

1. Keeping documentation, packaging metadata, and generated MCP manifests coherent with the live tool surface.
2. Adding continuous integration for unit tests and static checks.
3. Separating provider access from TrendPulse's domain logic so providers can be changed without rewriting the MCP layer.
4. Adding a production remote HTTP transport while preserving local stdio operation.
5. Designing a smaller high-level hosted tool surface for ChatGPT/Codex.
6. Integrating the hosted service with the DigestSEO application and operational stack.
7. Packaging and testing the hosted MCP as an OpenAI plugin only after the service is production-ready.

License

MIT. See LICENSE.