/claude-to-medrixflow

name: claude-to-medrixflow
description: "Interact with MedrixFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to MedrixFlow for research/analysis, start a MedrixFlow conversation thread, check MedrixFlow status or health, list available models/skills/agents in MedrixFlow, manage MedrixFlow memory, upload files to MedrixFlow threads, or delegate complex research tasks to MedrixFlow. Also use when the user mentions medrix_flow or wants to run a deep research task that MedrixFlow can handle."

MedrixFlow Skill

Communicate with a running MedrixFlow instance via its HTTP API. MedrixFlow is an AI agent platform built on LangGraph that orchestrates sub-agents for research, code execution, web browsing, and more.

Architecture

MedrixFlow exposes two API surfaces behind an Nginx reverse proxy:

| Service | Direct Port | Via Proxy | Purpose | |----------------|-------------|----------------------------------|----------------------------------| | Gateway API | 8001 | `$MEDRIXFLOW_GATEWAY_URL` | REST endpoints (models, skills, memory, uploads) | | LangGraph API | 2024 | `$MEDRIXFLOW_LANGGRAPH_URL` | Agent threads, runs, streaming |

Environment Variables

All URLs are configurable via environment variables. **Read these env vars before making any request.**

| Variable | Default | Description | |-------------------------|------------------------------------------|------------------------------------| | `MEDRIXFLOW_URL` | `http://localhost:2026` | Unified proxy base URL | | `MEDRIXFLOW_GATEWAY_URL` | `${MEDRIXFLOW_URL}` | Gateway API base (models, skills, memory, uploads) | | `MEDRIXFLOW_LANGGRAPH_URL`| `${MEDRIXFLOW_URL}/api/langgraph` | LangGraph API base (threads, runs) |

When making curl calls, always resolve the URL like this:

# Resolve base URLs from env (do this FIRST before any API call)
MEDRIXFLOW_URL="${MEDRIXFLOW_URL:-http://localhost:2026}"
MEDRIXFLOW_GATEWAY_URL="${MEDRIXFLOW_GATEWAY_URL:-$MEDRIXFLOW_URL}"
MEDRIXFLOW_LANGGRAPH_URL="${MEDRIXFLOW_LANGGRAPH_URL:-$MEDRIXFLOW_URL/api/langgraph}"

Available Operations

1. Health Check

Verify MedrixFlow is running:

curl -s "$MEDRIXFLOW_GATEWAY_URL/health"

2. Send a Message (Streaming)

This is the primary operation. It creates a thread and streams the agent's response.

**Step 1: Create a thread**

curl -s -X POST "$MEDRIXFLOW_LANGGRAPH_URL/threads" \
  -H "Content-Type: application/json" \
  -d '{}'

Response: `{"thread_id": "<uuid>", ...}`

**Step 2: Stream a run**

curl -s -N -X POST "$MEDRIXFLOW_LANGGRAPH_URL/threads/<thread_id>/runs/stream" \
  -H "Content-Type: application/json" \
  -d '{
    "assistant_id": "lead_agent",
    "input": {
      "messages": [
        {
          "type": "human",
          "content": [{"type": "text", "text": "YOUR MESSAGE HERE"}]
        }
      ]
    },
    "stream_mode": ["values", "messages-tuple"],
    "stream_subgraphs": true,
    "config": {
      "recursion_limit": 1000
    },
    "context": {
      "thinking_enabled": true,
      "is_plan_mode": true,
      "subagent_enabled": true,
      "thread_id": "<thread_id>"
    }
  }'

The response is an SSE stream. Each event has the format:

event: <event_type>
data: <json_data>

Key event types:

• `metadata` — run metadata including `run_id`
• `values` — full state snapshot with `messages` array
• `messages-tuple` — incremental message updates (AI text chunks, tool calls, tool results)
• `end` — stream is complete

**Context modes** (set via `context`):

• Flash mode: `thinking_enabled: false, is_plan_mode: false, subagent_enabled: false`
• Standard mode: `thinking_enabled: true, is_plan_mode: false, subagent_enabled: false`
• Pro mode: `thinking_enabled: true, is_plan_mode: true, subagent_enabled: false`
• Ultra mode: `thinking_enabled: true, is_plan_mode: true, subagent_enabled: true`

3. Continue a Conversation

To send follow-up messages, reuse the same `thread_id` from step 2 and POST another run with the new message.

4. List Models

curl -s "$MEDRIXFLOW_GATEWAY_URL/api/models"

Returns: `{"models": [{"name": "...", "provider": "...", ...}, ...]}`

5. List Skills

curl -s "$MEDRIXFLOW_GATEWAY_URL/api/skills"

Returns: `{"skills": [{"name": "...", "enabled": true, ...}, ...]}`

6. Enable/Disable a Skill

curl -s -X PUT "$MEDRIXFLOW_GATEWAY_URL/api/skills/<skill_name>" \
  -H "Content-Type: application/json" \
  -d '{"enabled": true}'

7. List Agents

curl -s "$MEDRIXFLOW_GATEWAY_URL/api/agents"

Returns: `{"agents": [{"name": "...", ...}, ...]}`

8. Get Memory

curl -s "$MEDRIXFLOW_GATEWAY_URL/api/memory"

Returns user context, facts, and conversation history summaries.

9. Upload Files to a Thread

curl -s -X POST "$MEDRIXFLOW_GATEWAY_URL/api/threads/<thread_id>/uploads" \
  -F "files=@/path/to/file.pdf"

Supports PDF, PPTX, XLSX, DOCX — automatically converts to Markdown.

10. List Uploaded Files

curl -s "$MEDRIXFLOW_GATEWAY_URL/api/threads/<thread_id>/uploads/list"

11. Get Thread History

curl -s "$MEDRIXFLOW_LANGGRAPH_URL/threads/<thread_id>/history"

12. List Threads

curl -s -X POST "$MEDRIXFLOW_LANGGRAPH_URL/threads/search" \
  -H "Content-Type: application/json" \
  -d '{"limit": 20, "sort_by": "updated_at", "sort_order": "desc"}'

Usage Script

For sending messages and collecting the full response, use the helper script:

bash /path/to/skills/claude-to-medrix_flow/scripts/chat.sh "Your question here"

See `scripts/chat.sh` for the implementation. The script: 1. Checks health 2. Creates a thread 3. Streams the