Click on "Deploy 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., "@LocalPulse Edge Analyze comments.csv for risk signals and show me top priorities"
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.
LocalPulse Edge is a privacy-first local MCP service for turning user-authorized CSV, JSON, or XLSX comment exports into risk signals, prioritized comments, evidence-backed actions, and local reports.
This public source release intentionally contains no trained model weights, real comment exports, annotations, runtime logs, competition handoff material, or machine-specific configuration. The included demo/demo_comments.csv is synthetic demonstration data.
python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install -r requirements.txt
python scripts\run_demo.pyRun the local MCP service over Streamable HTTP:
python scripts\run_mcp.py --transport streamable-http --host 127.0.0.1 --port 8890The service endpoint is http://127.0.0.1:8890/mcp. It listens only on the local machine in the example above.
Related MCP server: salesforce-deployment-guard
Open PowerShell in the project directory and run:
powershell -ExecutionPolicy Bypass -File scripts\install_trae_mcp.ps1 -ProjectRoot .The script starts and verifies the local MCP service, writes a JSON configuration under artifacts/, and opens Trae's import link.
In Trae, confirm the import and enable the project Skill at .trae/skills/localpulse/SKILL.md.
If the link cannot be opened, paste the contents of .trae/localpulse.http.mcp.json into Trae's MCP configuration UI. This release uses a standard HTTP MCP server; it does not require NPX or UVX packaging.
Without local model assets, the service remains usable for schema validation, cleaning, provenance, and deterministic fallback behavior. To enable hardware-accelerated inference, place independently obtained compatible assets outside version control and configure their paths with LOCALPULSE_* environment variables. Always use each analysis result's runtime evidence to distinguish model execution from fallback.
Analyze only comment exports the operator is authorized to use.
URLs are recognized as provenance only; LocalPulse does not log in to platforms, use cookies, or scrape comments.
Do not expose an unauthenticated MCP endpoint to the public Internet.
python -m pytest -q
python scripts\verify_mcp.py --transport streamable-http --port 8890
python scripts\package_skill.py --output artifacts\localpulse-skill-trae.zipMIT. See LICENSE.
This server cannot be deployed
Screens public GitHub repos and PRs to generate risk maps, findings, and merge-readiness signals.
Free data export guides for 11 platforms, export wait times, and in-browser viewers. No auth.
Live X/Twitter and Reddit research. 10 read-only MCP tools, Google/GitHub sign-in. Free tier.
Compliance & security scan for your app: secrets, exposed files, headers, privacy, AI-disclosure.
