# Langfuse — MCP server on mcp.ai
> Connect your Langfuse account and use 13 tools for developer tools straight from your AI agent. Connect with your own API key. Open source LLM engineering platform. Traces, evals, prompt management and metrics to debug and improve your LLM application.

By: mcp.ai · official
Page: https://mcp.ai/langfuse

## Connect (MCP protocol)
Remote MCP endpoint (HTTP, streamable): https://api.mcp.ai/p_langfuse?ms=1787293500000
Add it as a custom/remote MCP connector, then authenticate when prompted.

## REST API (no MCP client required)
Every tool is also a REST endpoint, authed with a workspace API key.
Discover: GET https://api.mcp.ai/api/langfuse/_endpoints   # public; lists every endpoint
Call:     POST https://api.mcp.ai/api/langfuse/<endpoint>
  Authorization: Bearer sk_live_…   # create one at https://mcp.ai/settings/api-keys
  Content-Type: application/json
  Body: { …args }   →   { "ok": true, "tool": "<id>", "result": { … } }

## Developer docs
How to use (MCP or REST), markdown: https://mcp.ai/langfuse/skill.md
Postman collection (v2.1): https://mcp.ai/langfuse/postman.json

## Tools
- langfuse_create_score(name: string, value: integer|number|string, source?: string, comment?: string, metadata?: object, queue_id?: string, score_id?: string, trace_id?: string, config_id?: string, data_type?: string, session_id?: string, environment?: string, dataset_run_id?: string, observation_id?: string) — Attach an evaluation score to exactly one Langfuse trace, session, or dataset run, optionally narrowing a trace score to an observation.
- langfuse_get_annotation_queue(queue_id: string) — Retrieve one Langfuse annotation queue by its ID.
- langfuse_get_prompt(label?: string, resolve?: boolean, version?: integer, prompt_name: string) — Retrieve a Langfuse text or chat prompt by name, deployment label, or exact version, with optional dependency resolution.
- langfuse_list_annotation_queues(limit?: integer, next_cursor?: string) — List annotation queues configured for human evaluation in the connected Langfuse project.
- langfuse_list_dataset_items(limit?: integer, version?: string, next_cursor?: string, dataset_name?: string, source_trace_id?: string, source_observation_id?: string) — List dataset items, optionally scoped to a dataset, source trace or observation, or historical dataset version.
- langfuse_list_dataset_run_items(page?: integer, limit?: integer, runName: string, datasetId: string) — List run items for a specific Langfuse dataset and run name.
- langfuse_list_datasets(limit?: integer, next_cursor?: string) — List datasets available to the connected Langfuse project.
- langfuse_list_experiments(limit?: integer, names?: string, fields?: string, dataset_ids?: string, filter_json?: string, next_cursor?: string, score_limit?: integer, to_start_time?: string, experiment_ids?: string, from_start_time: string) — List Langfuse experiments active in a required time range, optionally including metadata and directly attached scores.
- langfuse_list_models(limit?: integer, next_cursor?: string) — List Langfuse-managed and project-custom model pricing definitions used for usage and cost calculation.
- langfuse_list_observations(name?: string, level?: string, limit?: integer, fields?: string, user_id?: string, version?: string, trace_id?: string, session_id?: string, filter_json?: string, next_cursor?: string, environments?: string[], to_start_time?: string, expand_metadata?: string, from_start_time?: string, observation_type?: string, is_root_observation?: boolean, parent_observation_id?: string) — Search Langfuse observations such as generations, spans, events, agents, and tool calls, selecting only the field groups needed.
- langfuse_list_scores(limit?: integer, names?: string[], fields?: string[], values?: string[], sources?: string[], queue_ids?: string[], score_ids?: string[], trace_ids?: string[], value_max?: number, value_min?: number, config_ids?: string[], data_types?: string[], next_cursor?: string, session_ids?: string[], environments?: string[], to_timestamp?: string, experiment_ids?: string[], from_timestamp?: string, author_user_ids?: string[], observation_ids?: string[]) — Search numeric, boolean, categorical, text, and correction scores with subject and annotation context.
- langfuse_query_metrics(view: string, filters?: object[], metrics: object[], order_by?: object[], row_limit?: integer, dimensions?: object[], to_timestamp: string, from_timestamp: string, histogram_bins?: integer, time_granularity?: string) — Run an aggregate Langfuse metrics query over observations or numeric, boolean, or categorical scores.
- langfuse_upsert_llm_connection(config?: object, adapter: string, baseURL?: string, provider: string, secretKey: string, customModels?: string[], extraHeaders?: object, withDefaultModels?: boolean) — Create or update a Langfuse LLM provider connection by provider name.

## Example prompts
- "What can I do in Langfuse?"
- "Show me a summary of my Langfuse account"

## Links
Docs: https://mcp.ai/docs/mcps/langfuse
Website: https://mcp.ai/mcps/langfuse