LangWatch MCP Server

MCP server that gives AI coding agents access to LangWatch observability data, prompts, datasets, scenarios, evaluators, and documentation via the Model Context Protocol.

Quick Setup

Add to your MCP client configuration (Claude Code, Cursor, etc.):

{
  "mcpServers": {
    "langwatch": {
      "command": "npx",
      "args": ["-y", "@langwatch/mcp-server"],
      "env": {
        "LANGWATCH_API_KEY": "your-api-key-here"
      }
    }
  }
}

For Claude Code, you can also run:

claude mcp add langwatch -- npx -y @langwatch/mcp-server --apiKey your-api-key-here

The API key is required for observability and prompt tools. Documentation tools work without it.

Configuration

| Env Var | CLI Arg | Description | |---------|---------|-------------| | LANGWATCH_API_KEY | --apiKey | API key for authentication | | LANGWATCH_ENDPOINT | --endpoint | API endpoint (default: https://app.langwatch.ai) |

Tools

Documentation

| Tool | Description | |------|-------------| | fetch_langwatch_docs | Fetch LangWatch integration docs | | fetch_scenario_docs | Fetch Scenario agent testing docs |

Observability (requires API key)

| Tool | Description | |------|-------------| | discover_schema | Explore available filters, metrics, aggregations, and groups | | search_traces | Search traces with filters, text query, and date range | | get_trace | Get full trace details with AI-readable formatting | | get_analytics | Query timeseries analytics data |

Prompts (requires API key)

| Tool | Description | |------|-------------| | platform_list_prompts | List all prompts | | platform_get_prompt | Get prompt with messages and version history | | platform_create_prompt | Create a new prompt | | platform_update_prompt | Update prompt or create new version |

Datasets (requires API key)

| Tool | Description | |------|-------------| | platform_list_datasets | List all datasets with record counts | | platform_get_dataset | Get dataset metadata, columns, and record preview | | platform_create_dataset | Create a new dataset with optional column definitions | | platform_update_dataset | Update dataset name or column types | | platform_delete_dataset | Archive a dataset | | platform_create_dataset_records | Add records to a dataset (max 1000 per call) | | platform_update_dataset_record | Update a single record | | platform_delete_dataset_records | Delete records by IDs (max 1000 per call) |

Scenarios (requires API key)

| Tool | Description | |------|-------------| | platform_list_scenarios | List all scenarios | | platform_get_scenario | Get scenario details | | platform_create_scenario | Create a new scenario | | platform_update_scenario | Update a scenario | | platform_archive_scenario | Archive a scenario |

Evaluators (requires API key)

| Tool | Description | |------|-------------| | platform_list_evaluators | List all evaluators | | platform_get_evaluator | Get evaluator details | | platform_create_evaluator | Create a new evaluator | | platform_update_evaluator | Update an evaluator |

Model Providers (requires API key)

| Tool | Description | |------|-------------| | platform_list_model_providers | List configured model providers | | platform_set_model_provider | Configure a model provider |

Output Formats

Several tools support a format parameter:

• digest (default) — AI-readable markdown output. Optimized for LLM consumption — compact and information-dense.
• json — Full raw data. Useful for programmatic access or when you need the complete schema.

Supported on: search_traces, get_trace, platform_list_datasets, platform_get_dataset, platform_list_scenarios, platform_get_scenario.

Usage Tips

• Start with discover_schema to understand available filter fields and metrics.
• Use search_traces to find relevant traces, then get_trace for full details.
• Search returns 25 traces per page by default. Use scrollId from the response to paginate.
• Analytics uses category.name format for metrics (e.g., performance.completion_time).
• Use create_prompt / update_prompt with createVersion: true for safe prompt iteration.
• Use platform_list_datasets then platform_get_dataset to browse dataset contents.
• Dataset tools support full CRUD: create datasets, add/update/delete records, and archive datasets.

Development

Prerequisites

• Node.js 18+
• pnpm

Setup

pnpm install

Build

pnpm build

Test

pnpm test        # Run all tests
pnpm test:unit   # Unit tests only

Local testing

Build and point your MCP client to the local dist:

{
  "mcpServers": {
    "langwatch": {
      "command": "node",
      "args": [
        "/path/to/mcp-server/dist/index.js",
        "--apiKey", "your-api-key",
        "--endpoint", "http://localhost:5560"
      ]
    }
  }
}

Support

• Discord Community
• LangWatch Docs
• Email Support