Analytics
Langfuse MCP connector
The Langfuse connector brings your datasets, annotation queues, comments and review assignments into Claude, ChatGPT, Cursor and the Elaichi Agent, so your team can ask about them, add to them and tidy them in plain language.
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How it connects. Connects with an API key. The credential goes into a vault nobody reads back.
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One address. https://api.elaichi.ai/mcp, the same for every user.
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Their own access. An agent never gets more than the person it acts for.
How to connect
How to connect Langfuse to Claude, ChatGPT or Cursor
Two steps, about a minute.
In Elaichi
Connect Langfuse once
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Open Connections, choose Add connection, and pick Langfuse.
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Optionally set Share with to give a team access, then press Connect.
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Paste a Langfuse API key. One person generates a token in Langfuse and pastes it once. Everyone else works through Share with, and never sees it.
The credential is vaulted. Nobody reads it back, not even the AI.
Add connection
Choose a connector.
In your AI client
Point it at one endpoint
Everyone in the organization uses the same address, and each person only ever reaches what their own account allows.
Connect Langfuse to Claude
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1
Open Customize, then Connectors.
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2
Press Add.
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3
Name it, paste the MCP server URL, then Continue.
https://api.elaichi.ai/mcp -
4
Sign in and approve.
On Team and Enterprise, an Owner adds it once. Everyone else turns it on for themselves.
Connect Langfuse to ChatGPT
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1
Open Plugins, then press the + button.
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2
Name it and paste the endpoint into Server URL.
https://api.elaichi.ai/mcp -
3
Leave Authentication on OAuth, then tick the risk acknowledgement.
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4
Press Create, then sign in and approve.
Works on the web today. The plugin directory lives at chatgpt.com/plugins.
Connect Langfuse to Cursor
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1
Open
~/.cursor/mcp.json. -
2
Add the endpoint under
mcpServers.https://api.elaichi.ai/mcp -
3
Reload Cursor, then sign in and approve.
~/.cursor/mcp.json
{
"mcpServers": {
"elaichi": {
"url": "https://api.elaichi.ai/mcp"
}
}
}
Set up per machine, so repeat it on each computer you work from.
Connect Langfuse to any MCP client
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1
Add the endpoint as a remote MCP server.
https://api.elaichi.ai/mcp -
2
Sign in and approve.
{
"mcpServers": {
"elaichi": {
"url": "https://api.elaichi.ai/mcp"
}
}
}
The Elaichi Agent already has these tools, with nothing to set up.
Use cases
What teams do with Langfuse through Elaichi
Every one of these runs inside the access the person already has, and lands in the same audit log.
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AI engineering
Turn a real conversation into a test case
After spotting a bad answer in production, add it to a Langfuse dataset as a new item with the expected output, without leaving the chat where you found it.
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Quality
Queue outputs for human review
Create a Langfuse annotation queue for this week's release, add the traces that need eyes on them, and assign each reviewer their share.
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Product
Check what is waiting for review
Ask how many items are still open in a Langfuse annotation queue and who they are assigned to before the weekly quality meeting.
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Data
Record how an evaluation run went
Log dataset run items in Langfuse as a batch of test cases finishes, so every run is tied back to the dataset it came from.
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Research
Leave notes on traces for the team
Add a comment to a Langfuse trace or observation explaining why the output was wrong, so the next person reading it has context.
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Operations
Clean up finished review work
Mark reviewed Langfuse queue items as done, remove stale assignments in bulk, and retire dataset items that no longer reflect the product.
Try asking
- “List open annotation queue items assigned to the eval team”
- “Create an annotation queue for last week's flagged traces”
- “Which blob storage integrations are configured in Langfuse?”
AI tools
Langfuse tools for your AI agents
100 tools are ready to call through Elaichi's MCP endpoint the moment you connect Langfuse, governed by the same roles, restrictions, and audit log as everything else in Elaichi.
No tools match your search.
See it in Elaichi
What connecting Langfuse gets you
6 screens from the product, each doing one job for your Langfuse account.
The agent
Ask about annotation queues in plain language.
Elaichi's agent answers from live Langfuse queues, items and assignments.
- annotation queues
- queue items
- assignments
- blob storages
Ask Elaichi to work across your apps.
List open annotation queue items assigned to the eval team
Create an annotation queue for last week's flagged traces
Which blob storage integrations are configured in Langfuse?
Also runs in Claude, ChatGPT or Cursor
MCP clients
Claude, ChatGPT and Cursor reach Langfuse.
One org MCP endpoint over OAuth, no SDK and no shared API key.
Copy the endpoint
Tool catalog
100 Langfuse tools ready to call.
Queues, queue items, assignments and blob storages, with no custom code written.
- List all Langfuse public annotation queues
- Create a Langfuse public annotation queue
- Get single Langfuse public annotation queue by ID
- List all Langfuse annotation queue items
Toolboxes
Every team gets its own Langfuse toolbox.
Curate one toolbox for evaluation, another for platform, each scoped to that team.
- Evaluation
- ML Engineering
- Platform
- Data Science
Shared connections
Teammates use Langfuse without seeing a key.
The connections table shows who connected each Langfuse account and its sharing reach.
- Eval Prod
- ML Engineering
- Platform
- Data Science
Audit log
Answer who touched which queue item.
Append-only log of when, who, what happened, type and Langfuse resource.
- When
- Who
- What happened
- Type
Launching soon
From answering questions to doing the work
A person no longer has to ask. A trigger starts the work, inside the same permissions and the same audit log as everything else. Automations and live dashboards are launching soon, on the Black plan.
Automations
A schedule drafts your Langfuse digest.
Six steps fetch queue items, group them, draft, wait for approval, then post back.
Langfuse digest
Run 418 · started 2 minutes ago · on behalf of Emma Laurent
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✓
Schedule
Every weekday at 08:00
0.2s -
✓
Fetch annotation queues
Langfuse
1.4s -
✓
Group by owner
Transform
0.1s -
✓
Draft the digest
Agent step
Ran with 4 tools, returned a structured summary
6.2s -
Approve the digest
Needs approval
Assigned to Michael Brennan
Approve Deny -
Post the digest
Langfuse
Queued
Collections and dashboards
Langfuse queue health, computed on a schedule.
Four metrics, 14 days of items created, and a breakdown by team.
Langfuse health
Refreshed 4 minutes ago · every 15 minutes · from the annotation queues collection
Annotation queues
1,284 ↓ 12%
Queue items
96 ↓ 8%
Needs attention
3 ↑ 2
Updated this week
412 ↑ 9%
Annotation queues created
Last 14 days
By team
Share of activity
Eval Prod 34%
ML Engineering 27%
Platform 21%
Data Science 18%
Related connectors
More from the catalog
FAQ
Frequently asked questions
How do I connect Langfuse to Claude?
Connect Langfuse in Elaichi by pasting an API key from your Langfuse project settings. There is no OAuth application to register and no client ID or secret to generate. Then in Claude go to Customize, then Connectors, then Add, and paste https://api.elaichi.ai/mcp. Sign in with your Elaichi account and Langfuse is available in the chat.
Does Langfuse work with ChatGPT and Cursor as well as Claude?
Yes. Once Langfuse is connected in Elaichi, the same endpoint, https://api.elaichi.ai/mcp, works in Claude, ChatGPT, Cursor, any other MCP client and the Elaichi Agent. You connect Langfuse once and every client picks it up.
What can an AI agent actually do with my Langfuse data?
With Langfuse connected, an agent can list your datasets and pull up individual dataset items, add new items and dataset run items, create annotation queues, add items to them and assign reviewers, and read or leave comments on traces. Because Langfuse exposes a lot of actions, the agent looks them up as needed, so short concrete asks like "add this to the regression dataset" work better than long paragraphs.
Does connecting Langfuse give the AI access to every project?
No. The connection runs inside whatever the Langfuse API key you pasted can already see, typically one project, and the agent gets nothing beyond that. Elaichi can narrow access further, for example read only on datasets, but it can never widen what Langfuse itself allows.
Can I stop an agent from deleting or changing things in Langfuse?
Yes. Restrictions in Elaichi work per action, so you can allow reading Langfuse datasets and queues while blocking deletes of dataset items, queue items or assignments. A blocked action is never shown to Claude, ChatGPT, Cursor or any other client, so no prompt can reach it.
What happens to a Langfuse connection when someone leaves?
When a person is offboarded in Elaichi, their access to Langfuse through every client ends at once. A Langfuse connection they shared keeps working for everyone else on the team. If you want to remove Langfuse entirely, disconnecting it once in Elaichi removes it from Claude, ChatGPT, Cursor and the Elaichi Agent together.
Put Langfuse in front of your team
Fourteen days on Gold, no credit card. Connect it once and pick what each team can call.