Content
# Langfuse MCP Server
[](https://badge.fury.io/py/langfuse-mcp)
[](https://pepy.tech/projects/langfuse-mcp)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[Model Context Protocol](https://modelcontextprotocol.io) server for [Langfuse](https://langfuse.com) observability. Query traces, debug errors, analyze sessions, manage prompts.
## Why langfuse-mcp?
Comparison with [official Langfuse MCP](https://github.com/langfuse/mcp-server-langfuse) (as of Jan 2026):
| | langfuse-mcp | Official |
|-|--------------|----------|
| **Traces & Observations** | Yes | No |
| **Sessions & Users** | Yes | No |
| **Exception Tracking** | Yes | No |
| **Prompt Management** | Yes | Yes |
| **Dataset Management** | Yes | No |
| **Annotation Queues** | Yes | No |
| **Scores (v2)** | Yes | No |
| **Selective Tool Loading** | Yes | No |
This project provides a **full observability toolkit** — traces, observations, sessions, exceptions, prompts, datasets, annotation queues, and scores — while the official MCP focuses on prompt management.
## Quick Start
Requires [uv](https://docs.astral.sh/uv/getting-started/installation/) (for `uvx`) and Python 3.10 or newer. CI verifies Python 3.10 through 3.14.
Get credentials from [Langfuse Cloud](https://cloud.langfuse.com) → Settings → API Keys. If self-hosted, use your instance URL for `LANGFUSE_HOST`.
```bash
# Claude Code (project-scoped, shared via .mcp.json)
claude mcp add \
-e LANGFUSE_PUBLIC_KEY=pk-... \
-e LANGFUSE_SECRET_KEY=sk-... \
-e LANGFUSE_HOST=https://cloud.langfuse.com \
--scope project \
langfuse -- uvx langfuse-mcp
# Codex CLI (user-scoped, stored in ~/.codex/config.toml)
codex mcp add langfuse \
--env LANGFUSE_PUBLIC_KEY=pk-... \
--env LANGFUSE_SECRET_KEY=sk-... \
--env LANGFUSE_HOST=https://cloud.langfuse.com \
-- uvx langfuse-mcp
```
To pin a CI-verified interpreter explicitly, add `--python 3.14` before `langfuse-mcp`.
Restart your CLI, then verify with `/mcp` (Claude Code) or `codex mcp list` (Codex).
## Tools (37 total)
| Category | Tools |
|----------|-------|
| Traces | `fetch_traces`, `fetch_trace` |
| Observations | `fetch_observations`, `fetch_observation` |
| Sessions | `fetch_sessions`, `get_session_details`, `get_user_sessions` |
| Exceptions | `find_exceptions`, `find_exceptions_in_file`, `get_exception_details`, `get_error_count` |
| Prompts | `list_prompts`, `get_prompt`, `get_prompt_unresolved`, `create_text_prompt`, `create_chat_prompt`, `update_prompt_labels` |
| Datasets | `list_datasets`, `get_dataset`, `list_dataset_items`, `get_dataset_item`, `create_dataset`, `create_dataset_item`, `delete_dataset_item` |
| Annotation Queues | `list_annotation_queues`, `create_annotation_queue`, `get_annotation_queue`, `list_annotation_queue_items`, `get_annotation_queue_item`, `create_annotation_queue_item`, `update_annotation_queue_item`, `delete_annotation_queue_item`, `create_annotation_queue_assignment`, `delete_annotation_queue_assignment` |
| Scores | `list_scores_v2`, `get_score_v2` |
| Schema | `get_data_schema` |
## Dataset Item Updates (Upsert)
Langfuse uses upsert for dataset items. To edit an existing item, call `create_dataset_item` with `item_id`. If the ID exists, it updates; otherwise it creates a new item.
```python
create_dataset_item(
dataset_name="qa-test-cases",
item_id="item_123",
input={"question": "What is 2+2?"},
expected_output={"answer": "4"}
)
```
## Skill
This project includes a skill with debugging playbooks.
**Via [skills](https://github.com/vercel-labs/add-skill)** (recommended):
```bash
npx skills add avivsinai/langfuse-mcp -g -y
```
**Via [skild](https://skild.sh)**:
```bash
npx skild install @avivsinai/langfuse -t claude -y
```
**Manual install:**
```bash
cp -r skills/langfuse ~/.claude/skills/ # Claude Code
cp -r skills/langfuse ~/.codex/skills/ # Codex CLI
```
Try asking: "help me debug langfuse traces"
See [`skills/langfuse/SKILL.md`](skills/langfuse/SKILL.md) for full documentation.
## Selective Tool Loading
Load only the tool groups you need to reduce token overhead:
```bash
langfuse-mcp --tools traces,prompts
```
Available groups: `traces`, `observations`, `sessions`, `exceptions`, `prompts`, `datasets`, `annotation_queues`, `scores`, `schema`
## Read-Only Mode
Disable all write operations for safer read-only access:
```bash
langfuse-mcp --read-only
# Or via environment variable
LANGFUSE_MCP_READ_ONLY=true langfuse-mcp
```
This disables: `create_text_prompt`, `create_chat_prompt`, `update_prompt_labels`, `create_dataset`, `create_dataset_item`, `delete_dataset_item`, `create_annotation_queue`, `create_annotation_queue_item`, `update_annotation_queue_item`, `delete_annotation_queue_item`, `create_annotation_queue_assignment`, `delete_annotation_queue_assignment`
## Default Output Mode
Set the MCP-exposed default `output_mode` so clients that omit the parameter automatically use your preferred mode:
```bash
langfuse-mcp --default-output-mode full_json_file
# Or via environment variable
LANGFUSE_MCP_DEFAULT_OUTPUT_MODE=full_json_file langfuse-mcp
```
Supported values: `compact`, `full_json_string`, `full_json_file`
This updates the default shown in MCP tool schemas. Clients can still override it per call by passing `output_mode` explicitly.
## Other Clients
### Cursor
Create `.cursor/mcp.json` in your project (or `~/.cursor/mcp.json` for global):
```json
{
"mcpServers": {
"langfuse": {
"command": "uvx",
"args": ["langfuse-mcp"],
"env": {
"LANGFUSE_PUBLIC_KEY": "pk-...",
"LANGFUSE_SECRET_KEY": "sk-...",
"LANGFUSE_HOST": "https://cloud.langfuse.com",
"LANGFUSE_MCP_DEFAULT_OUTPUT_MODE": "full_json_file"
}
}
}
}
```
### Docker
```bash
docker run --rm -i \
-e LANGFUSE_PUBLIC_KEY=pk-... \
-e LANGFUSE_SECRET_KEY=sk-... \
-e LANGFUSE_HOST=https://cloud.langfuse.com \
ghcr.io/avivsinai/langfuse-mcp:latest
```
### Optional environment variables
| Variable | Default | Description |
|---|---|---|
| `LANGFUSE_MAX_AGE_DAYS` | `7` | Caps the lookback window for time-based tools (`fetch_traces`, `fetch_observations`, etc.). Set to match your Langfuse instance's data retention — e.g. `30` if your retention is 30 days. |
## Development
```bash
uv venv --python 3.14 .venv && source .venv/bin/activate
uv pip install -e ".[dev]"
pytest
```
## License
MIT
