Alfresco Agents Lab Clive

Alfresco Agents Lab (CLive)

[](https://www.docker.com/) [](https://www.python.org/) [](https://fastapi.tiangolo.com/) [](https://www.apache.org/licenses/LICENSE-2.0) [](https://www.llamaindex.ai/) [](https://github.com/Alfresco)

End-to-end lab to run Alfresco Community (with Markdown renditions) + an MCP server (with a Markdown tool) + a FastAPI Agent that consumes MCP tools through LlamaIndex. Everything can be started from the repo root with a single Compose file.

> The MCP tool added here follows the lab guide: "Add MCP Tool" in lab-material/add-mcp-tool.md

Repository layout

/
├─ alfresco-deployment/          # Complete Alfresco CE deployment (repo, solr, share, ACA, transforms, proxy)
│  ├─ compose.yaml
├─ alfresco-mcp-server/          # Containerized MCP server wired to Alfresco
│  ├─ compose.yaml
│  ├─ Dockerfile
│  └─ get_markdown_content.py    # Tool implementation (see “Added MCP tool”)
├─ fastapi-agent/                # FastAPI service (Agent) with LlamaIndex + MCP tools
│  ├─ compose.yaml
│  ├─ main.py
│  └─ dockerfile
├─ lab-material/
│  ├─ add-mcp-tool.md            # Step-by-step guide for adding the Markdown tool
│  └─ add-action-to-aca.md       # Step-by-step guide for adding a Summarizing action to ACA UI
└─ compose.yaml                  # Root Compose that includes the two sub-stacks + agent

Architecture

flowchart LR
  %% Entry
  U[User] -->|HTTP 8000| AGENT[AI Agent]

  %% AI Agent stack
  subgraph AI_Agent_Stack
    AGENT[AI Agent]
    MCP[Alfresco MCP]
    AGENT -->|HTTP 8003| MCP
    AGENT -->|HTTP 11434, gpt-oss| OLLAMA[Ollama runtime]
  end

  %% Alfresco core
  subgraph Alfresco_Repository
    REPO[Alfresco Repository]
    TMD[Transform MD convert2md]
    REPO -->|HTTP 8090| TMD
  end

  %% LLM runtime
  subgraph LLM
    OLLAMA[Ollama runtime]
  end

  %% Cross stack links
  MCP -->|HTTP 8080| REPO
  TMD -->|HTTP 11434,llava| OLLAMA

Running

1. Prereqs

• Docker Desktop / Engine with Docker Compose v2 (supports include: in compose.yaml)
• Ollama running on your host with required models

``bash # for the Markdown transformer ollama pull llava ollama pull mxbai-embed-large # for the agent (or change OLLAMA_MODEL in .env) ollama pull gpt-oss ``

Ollama should listen on http://localhost:11434 (used via host.docker.internal inside containers)

> Note: If you are using Linux, check the specific instructions at https://github.com/aborroy/alfresco-agents-lab-clive/issues/1#issuecomment-3391212961

1. Up the full stack from the repo root

docker compose up --build

1. Open the UIs

• Alfresco Content App: http://localhost:8080/
• Alfresco Repository: http://localhost:8080/alfresco/
• MCP Server (health/endpoint): http://localhost:8003/mcp
• Agent API (FastAPI): http://localhost:8000/ (health), POST /agent (run)

To login into Alfresco UI use the credentials

```` user = admin password = admin

````

Using the Agent

The Agent consumes MCP tools from alfresco-mcp-server and runs prompts with your chosen LLM

Run an agent turn, like in following samples

curl -sS http://localhost:8000/agent \
  -H "Content-Type: application/json" \
  -d '{"prompt":"What tools do you have?","instructions": "Be helpful and concise"}'

curl -sS http://localhost:8000/agent \
  -H "Content-Type: application/json" \
  -d '{"prompt":"Fetch Markdown for node 947c51e2-6ffd-4eb8-bc51-e26ffd1eb8b6 and summarize it"}'

Lab Guides

The repository includes practical tutorials:

| Guide | Description | | ------------------------------------------------------ | ------------------------------------------------------------------------------------ | | [Add MCP Tool](lab-material/add-mcp-tool.md) | Explains how to develop and register a new MCP tool to access Alfresco content | | [Add Action to ACA](lab-material/add-action-to-aca.md) | Describes how to extend Alfresco Content App to trigger the AI summarization process |

Each guide is designed to be followed independently, but together they form a complete learning path from zero to AI-enhanced Alfresco

Development Notes

You can rebuild or tweak individual components using their internal compose.yaml files

For example, to develop and test the MCP server alone:

cd alfresco-mcp-server
docker compose up --build

To run the FastAPI agent in local development mode:

cd fastapi-agent
uvicorn main:app --reload --port 8000

Related Resources

• Spring AI
• Model Context Protocol (MCP)
• LlamaIndex Documentation
• Ollama

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: aborroy
• Source: aborroy/alfresco-agents-lab-clive
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.