diff --git a/.github/workflows/pages.yml b/.github/workflows/pages.yml new file mode 100644 index 0000000..6b81519 --- /dev/null +++ b/.github/workflows/pages.yml @@ -0,0 +1,23 @@ +name: pages +on: + push: {branches: [main]} + workflow_dispatch: +permissions: {contents: read, pages: write, id-token: write} +concurrency: {group: pages, cancel-in-progress: true} +jobs: + build: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - run: mkdir -p _site && cp -r site/* _site/ && cp -r docs/screenshots _site/ && touch _site/.nojekyll + - uses: actions/upload-pages-artifact@v3 + with: {path: _site} + deploy: + needs: build + runs-on: ubuntu-latest + environment: + name: github-pages + url: ${{ steps.d.outputs.page_url }} + steps: + - id: d + uses: actions/deploy-pages@v4 diff --git a/README.md b/README.md index 6af8572..7dea6ca 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ # AgentOps MCP +**Live demo (static, GitHub Pages):** https://naveecode.github.io/agentops-mcp/ + [![ci](https://github.com/naveecode/agentops-mcp/actions/workflows/ci.yml/badge.svg)](https://github.com/naveecode/agentops-mcp/actions) A deployable AI agent service. A LangGraph ReAct agent answers questions over your documents and calls tools. The same tools are exposed as an **MCP server**, so Cursor and Claude Desktop can use them. Documents are chunked, embedded, and stored in MongoDB. Ingest runs inline, or through a RabbitMQ worker that retries and then dead-letters. diff --git a/site/index.html b/site/index.html new file mode 100644 index 0000000..e2490fe --- /dev/null +++ b/site/index.html @@ -0,0 +1,17 @@ + +AgentOps MCP demo + +

AgentOps MCP

+

A tool-calling LangGraph agent served by FastAPI with a Redis cache. The same tools are exposed as an MCP server for Cursor and Claude Desktop. Source on GitHub.

+

This is a static demo page. The live backend is not hosted; run it locally with docker compose up.

+

Chat UI

Chat UI, desktopChat UI, mobile
+

Architecture

flowchart LR
+  UI[Next.js chat UI] --> API[FastAPI /ask]
+  API --> C[(Redis cache)]
+  API --> AG[LangGraph ReAct agent]
+  AG --> T[Tools: search_docs, calculator]
+  MCP[MCP server stdio] --> T
+  API --> K[Docker / kind K8s]
+

Quickstart

git clone https://github.com/naveecode/agentops-mcp && cd agentops-mcp
+docker compose up        # API on :8000, Redis
+python -m app.mcp_server # MCP for Cursor / Claude