Langfuse MCP
MCP server for Langfuse. Query LLM trace data, sessions, and observations from inside agents for debugging and observability. 85 GitHub stars and 16 commits on main in the last 30 days.
“MCP server for Langfuse. Query LLM trace data, sessions, observations, and prompts from inside agents. 85 stars and 16 commits on main in the last 30 days.”
INSTALL THIS SERVER
{
"mcpServers": {
"langfuse": {
"command": "npx",
"args": [
"-y",
"langfuse-mcp"
],
"env": {
"LANGFUSE_PUBLIC_KEY": "pk-lf-...",
"LANGFUSE_SECRET_KEY": "sk-lf-...",
"LANGFUSE_HOST": "https://cloud.langfuse.com"
}
}
}
}
{
"mcpServers": {
"langfuse": {
"command": "npx",
"args": [
"-y",
"langfuse-mcp"
],
"env": {
"LANGFUSE_PUBLIC_KEY": "pk-lf-...",
"LANGFUSE_SECRET_KEY": "sk-lf-...",
"LANGFUSE_HOST": "https://cloud.langfuse.com"
}
}
}
}
{
"mcpServers": {
"langfuse": {
"command": "npx",
"args": [
"-y",
"langfuse-mcp"
],
"env": {
"LANGFUSE_PUBLIC_KEY": "pk-lf-...",
"LANGFUSE_SECRET_KEY": "sk-lf-...",
"LANGFUSE_HOST": "https://cloud.langfuse.com"
}
}
}
}
{
"mcpServers": {
"langfuse": {
"command": "npx",
"args": [
"-y",
"langfuse-mcp"
],
"env": {
"LANGFUSE_PUBLIC_KEY": "pk-lf-...",
"LANGFUSE_SECRET_KEY": "sk-lf-...",
"LANGFUSE_HOST": "https://cloud.langfuse.com"
}
}
}
}
{
"mcpServers": {
"langfuse": {
"command": "npx",
"args": [
"-y",
"langfuse-mcp"
],
"env": {
"LANGFUSE_PUBLIC_KEY": "pk-lf-...",
"LANGFUSE_SECRET_KEY": "sk-lf-...",
"LANGFUSE_HOST": "https://cloud.langfuse.com"
}
}
}
}
6 TOOLS AVAILABLE
OUR ASSESSMENT
- 85 GitHub stars.
- 16 commits on main in the last 30 days.
- MIT license.
- Active community development.
- Self-hosted Langfuse and Langfuse Cloud both supported.
- Pairs with arize-phoenix-mcp for full LLM observability coverage.
- Langfuse account or self-hosted instance required.
- Tool surface is read-only; trace creation runs through the Langfuse SDK, not this MCP.
- Community-maintained; no Langfuse vendor stamp.
Langfuse keys are project-scoped. Use a dedicated key per agent context. Trace data may contain prompts, completions, and PII; review the agent prompt path before mounting in production.
Teams using Langfuse for LLM observability who want agents to inspect their own traces; debugging-heavy agent workflows where the agent reads its own past behaviour; evaluation-driven development where scores feed back into agent decisions.
TECHNICAL DETAILS
ADOPTION METRICS
// Reading this85 stars on avivsinai/langfuse-mcp. 16 commits on main in the last 30 days.
// Reading thisPairs with Arize Phoenix, Datadog, Grafana, Prometheus, Sentry, PagerDuty, Axiom, Rollbar in monitoring. Adds LLM-specific observability slot.
SOURCES & VERIFICATION
We don't take any single directory's word for it. Before scoring, we cross-reference 4 public MCP sources, install the server ourselves against the clients we cover, and record when we last re-verified.
The same server, 4 different lenses. We reconcile these signals into our editorial score, which is why our number sometimes diverges from a directory-aggregate star count.
| Source | Their rating | Their star count | Their downloads | Last synced |
|---|---|---|---|---|
| AutomationSwitch This page | 4.3editorial | 85 | — | MAY 6, 2026 |
| PulseMCP | — unrated | unavailable | unavailable | MAY 6, 2026 |
| MCP.so | — unrated | unavailable | unavailable | MAY 6, 2026 |
| Glama | — unrated | unavailable | unavailable | MAY 6, 2026 |
| Smithery | — unrated | unavailable | unavailable | MAY 6, 2026 |
// Counts are directory-reported; we don't adjust them. Discrepancies usually come from different snapshot times or star-caching.
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DISCUSS YOUR
MCP REQUIREMENTS.
Evaluating a server, scoping an internal deployment, or working out whether MCP is the right fit at all. Start the conversation and we will point you at the right piece of the ecosystem.