What is the deployment process?
Documentation deploys automatically when changes are pushed to the `main` branch. GitHub Actions builds the site and publishes it to GitHub Pages. No manual deployment commands are needed.
@verlyn13
Basic information
An mcp server for my scopecam project.
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
The MCP Documentation Project contains the documentation for the Multi-agent Control Platform (MCP). It provides a GitHub Actions workflow for automatic deployment and a local Hugo development server for testing.
Make content changes on the main branch, test locally with hugo server if needed, then commit and push to main – GitHub Actions automatically builds and deploys the site to GitHub Pages. Manual deployment is not required.
mainDocumentation deploys automatically when changes are pushed to the `main` branch. GitHub Actions builds the site and publishes it to GitHub Pages. No manual deployment commands are needed.
Run `hugo server` in the repository root to build and serve the site locally. You can also use the legacy script `./deploy-docs.sh --build-only`.
The static site is hosted on GitHub Pages, using the repository’s configured GitHub Pages URL.
All source code, content, and configuration reside on the `main` branch. GitHub Actions handles building and deploying; the `gh-pages` branch (or other deployment branch) is not manually manipulated.
Check the Troubleshooting Guide in `content/project/github-actions-troubleshooting.md`, review the GitHub Actions logs in the repository’s Actions tab, or open an issue.
Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.

Serve your docs to AI agents over SSH and MCP. Agents use ls, cat, grep, find, and pipes against a virtual filesystem backed by your documentation. Identity-scoped access, governed writing with human approval, and portab

MCP connector for Snipara, the Project Brain for AI coding agents

Open-source Python SDK & MCP interface for Priostack Agent Context Network (ACN). Zero-setup, autonomous memory orchestration for AI agents.

Search saved employee handbooks from your AI assistant. Four read-only tools list authorized handbooks, browse policies, search content, and read source pages with citation links. Uses scoped bearer tokens and Streamable
Comments