🐑 Shepherd MCP

MCP (Model Context Protocol) server for Shepherd - Debug your AI agents like you debug your code.

This MCP server allows AI assistants (Claude, Cursor, etc.) to query and analyze your AI agent sessions from multiple observability providers.

Supported Providers

• AIOBS (Shepherd backend) - Native Shepherd observability

• Langfuse - Open-source LLM observability platform

Related MCP server: AgentLens MCP Server

Installation

pip install shepherd-mcp

Or run directly with uvx:

uvx shepherd-mcp

Configuration

Environment Variables

AIOBS (Shepherd)

• AIOBS_API_KEY (required) - Your Shepherd API key

• AIOBS_ENDPOINT (optional) - Custom API endpoint URL

Langfuse

• LANGFUSE_PUBLIC_KEY (required) - Your Langfuse public API key

• LANGFUSE_SECRET_KEY (required) - Your Langfuse secret API key

• LANGFUSE_HOST (optional) - Custom Langfuse host URL (defaults to cloud.langfuse.com)

.env File Support

shepherd-mcp automatically loads .env files from the current directory or any parent directory. This means if you have a .env file in your project root:

# .env
# AIOBS
AIOBS_API_KEY=aiobs_sk_xxxx

# Langfuse
LANGFUSE_PUBLIC_KEY=pk-lf-xxxx
LANGFUSE_SECRET_KEY=sk-lf-xxxx
LANGFUSE_HOST=https://cloud.langfuse.com

It will be automatically loaded when the MCP server starts.

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "shepherd": {
      "command": "uvx",
      "args": ["shepherd-mcp"],
      "env": {
        "AIOBS_API_KEY": "aiobs_sk_xxxx",
        "LANGFUSE_PUBLIC_KEY": "pk-lf-xxxx",
        "LANGFUSE_SECRET_KEY": "sk-lf-xxxx",
        "LANGFUSE_HOST": "https://cloud.langfuse.com"
      }
    }
  }
}

Cursor

Add to your .cursor/mcp.json:

{
  "mcpServers": {
    "shepherd": {
      "command": "uvx",
      "args": ["shepherd-mcp"],
      "env": {
        "AIOBS_API_KEY": "aiobs_sk_xxxx",
        "LANGFUSE_PUBLIC_KEY": "pk-lf-xxxx",
        "LANGFUSE_SECRET_KEY": "sk-lf-xxxx",
        "LANGFUSE_HOST": "https://cloud.langfuse.com"
      }
    }
  }
}

Or if installed via pip:

{
  "mcpServers": {
    "shepherd": {
      "command": "shepherd-mcp",
      "env": {
        "AIOBS_API_KEY": "aiobs_sk_xxxx",
        "LANGFUSE_PUBLIC_KEY": "pk-lf-xxxx",
        "LANGFUSE_SECRET_KEY": "sk-lf-xxxx",
        "LANGFUSE_HOST": "https://cloud.langfuse.com"
      }
    }
  }
}

Available Tools

AIOBS (Shepherd) Tools

aiobs_list_sessions

List all AI agent sessions from Shepherd.

Parameters:

• limit (optional): Maximum number of sessions to return

Example prompt:

"List my recent AI agent sessions from AIOBS"

aiobs_get_session

Get detailed information about a specific session including the full trace tree, LLM calls, function events, and evaluations.

Parameters:

• session_id (required): The UUID of the session to retrieve

Example prompt:

"Get AIOBS session details for abc123-def456"

aiobs_search_sessions

Search and filter sessions with multiple criteria.

Parameters:

• query (optional): Text search (matches name, ID, labels, metadata)

• labels (optional): Filter by labels as key-value pairs

• provider (optional): Filter by LLM provider (e.g., 'openai', 'anthropic')

• model (optional): Filter by model name (e.g., 'gpt-4o-mini', 'claude-3')

• function (optional): Filter by function name

• after (optional): Sessions started after date (YYYY-MM-DD)

• before (optional): Sessions started before date (YYYY-MM-DD)

• has_errors (optional): Only return sessions with errors

• evals_failed (optional): Only return sessions with failed evaluations

• limit (optional): Maximum number of sessions to return

Example prompts:

"Find all AIOBS sessions that used OpenAI with errors" "Search for sessions from yesterday that failed evaluations"

aiobs_diff_sessions

Compare two sessions and show their differences including:

• Metadata: Duration, labels, timestamps

• LLM calls: Count, tokens (input/output/total), average latency, errors

• Provider/Model distribution: Which providers and models were used

• Function events: Total calls, unique functions, function-specific counts

• Trace structure: Trace depth, root nodes

• Evaluations: Pass/fail counts and rates

• System prompts: Compare system prompts across sessions

• Request parameters: Temperature, max_tokens, tools used

• Response content: Content length, tool calls, stop reasons

Parameters:

• session_id_1 (required): First session UUID to compare

• session_id_2 (required): Second session UUID to compare

Example prompt:

"Compare AIOBS sessions abc123 and def456"

Langfuse Tools

langfuse_list_traces

List traces with pagination and filters. Traces represent complete workflows or conversations.

Parameters:

• limit (optional): Maximum results per page (default: 50)

• page (optional): Page number (1-indexed)

• user_id (optional): Filter by user ID

• name (optional): Filter by trace name

• session_id (optional): Filter by session ID

• tags (optional): Filter by tags

• from_timestamp (optional): Filter after timestamp

• to_timestamp (optional): Filter before timestamp

Example prompt:

"List the last 20 Langfuse traces"

langfuse_get_trace

Get a specific trace with its observations (generations, spans, events).

Parameters:

• trace_id (required): The trace ID to fetch

Example prompt:

"Get Langfuse trace details for trace-id-123"

langfuse_list_sessions

List sessions with pagination. Sessions group related traces together.

Parameters:

• limit (optional): Maximum results per page

• page (optional): Page number

• from_timestamp (optional): Filter after timestamp

• to_timestamp (optional): Filter before timestamp

Example prompt:

"Show me Langfuse sessions from the last week"

langfuse_get_session

Get a specific session with its metrics and traces.

Parameters:

• session_id (required): The session ID to fetch

Example prompt:

"Get Langfuse session details for session-123"

langfuse_list_observations

List observations (generations, spans, events) with filters.

Parameters:

• limit (optional): Maximum results per page

• page (optional): Page number

• name (optional): Filter by observation name

• user_id (optional): Filter by user ID

• trace_id (optional): Filter by trace ID

• type (optional): Filter by type (GENERATION, SPAN, EVENT)

• from_timestamp (optional): Filter after timestamp

• to_timestamp (optional): Filter before timestamp

Example prompt:

"List all GENERATION type observations from Langfuse"

langfuse_get_observation

Get a specific observation with full details including input, output, usage, and costs.

Parameters:

• observation_id (required): The observation ID to fetch

Example prompt:

"Get details for Langfuse observation obs-123"

langfuse_list_scores

List scores/evaluations with filters.

Parameters:

• limit (optional): Maximum results per page

• page (optional): Page number

• name (optional): Filter by score name

• user_id (optional): Filter by user ID

• trace_id (optional): Filter by trace ID

• from_timestamp (optional): Filter after timestamp

• to_timestamp (optional): Filter before timestamp

Example prompt:

"Show me Langfuse scores for trace trace-123"

langfuse_get_score

Get a specific score/evaluation with full details.

Parameters:

• score_id (required): The score ID to fetch

Example prompt:

"Get Langfuse score details for score-123"

Legacy Tools (Deprecated)

For backwards compatibility, the following tools are still available but will be removed in a future version:

• list_sessions → Use aiobs_list_sessions

• get_session → Use aiobs_get_session

• search_sessions → Use aiobs_search_sessions

• diff_sessions → Use aiobs_diff_sessions

Use Cases

1. Debugging Failed Runs

"Show me all AIOBS sessions that had errors in the last 24 hours"

2. Performance Analysis

"Compare AIOBS session abc123 with session def456 and tell me which one was more efficient"

3. Prompt Regression Detection

"Find Langfuse traces with failed evaluations"

4. Cost Tracking

"List Langfuse observations and summarize the total cost"

5. Session Inspection

"Get the full trace tree for the most recent Langfuse trace and explain what happened"

6. Cross-Provider Analysis

"Show me both AIOBS sessions and Langfuse traces from today"

Development

Setup

git clone https://github.com/neuralis/shepherd-mcp
cd shepherd-mcp
python -m venv venv
source venv/bin/activate
pip install -e ".[dev]"

Running Tests

pytest

Running Locally

export AIOBS_API_KEY=aiobs_sk_xxxx
export LANGFUSE_PUBLIC_KEY=pk-lf-xxxx
export LANGFUSE_SECRET_KEY=sk-lf-xxxx
python -m shepherd_mcp

Publishing to PyPI

Releases are automatically published to PyPI via GitHub Actions when a release is created.

To publish manually:

# Build the package
pip install build twine
python -m build

# Upload to PyPI
twine upload dist/*

Architecture

src/shepherd_mcp/
├── __init__.py          # Package exports
├── __main__.py          # Entry point
├── server.py            # MCP server with tool handlers
├── models/              # Data models
│   ├── __init__.py
│   ├── aiobs.py         # AIOBS-specific models
│   └── langfuse.py      # Langfuse-specific models
└── providers/           # Provider clients
    ├── __init__.py
    ├── base.py          # Base provider interface
    ├── aiobs.py         # AIOBS client implementation
    └── langfuse.py      # Langfuse client implementation

┌─────────────────┐     stdio      ┌─────────────────┐
│  Cursor/Claude  │ ◄────────────► │  shepherd-mcp   │
│    (Client)     │   stdin/stdout │   (subprocess)  │
└─────────────────┘                └────────┬────────┘
                                            │ HTTPS
                                  ┌─────────┴─────────┐
                                  │                   │
                                  ▼                   ▼
                         ┌─────────────┐     ┌─────────────┐
                         │ Shepherd API│     │ Langfuse API│
                         │   (AIOBS)   │     │   (Cloud)   │
                         └─────────────┘     └─────────────┘

License

MIT