Integration
Connect Langfuse and Rendobar
When New Trace fires in Langfuse, your agent runs Add asset in Rendobar, or Job completed in Rendobar to Add Comment in Langfuse. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want Langfuse and Rendobar to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)Langfuse records how your LLM app behaves; Rendobar transcodes, captions and watermarks media over REST. Connecting them means a finished Rendobar job can write scores, comments or dataset items back onto the Langfuse trace that asked for it, and a new Langfuse trace can kick off an asset upload or a processing job in Rendobar.
Example flows
What Langfuse and Rendobar can do together
From Langfuse to Rendobar
When New Trace in Langfuse
then Add asset in Rendobar
From Rendobar to Langfuse
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with Langfuse and Rendobar
Triggers and actions 2 triggers · 26 actions
- New Trace
Polling trigger: fires for newly created traces (dedup by trace id / timestamp).
- Add Comment
Add a comment to a trace/observation/session/prompt object.
- Add Dataset
Create a new dataset.
- Add Dataset Item
Create an item (input/expected_output/metadata) in a dataset.
- Add Prompt
Create a new prompt version (text or chat).
- Add Score
Create a score attached to a trace/observation/session (numeric, categorical, or boolean).
- Delete Trace
Delete a trace by id.
- Get Project
Reads the Langfuse project that the connection's project-scoped API key belongs to.
- Get Prompt
Get a prompt by name (and optional version/label).
- Get Trace
Get a single trace by id, including nested observations/scores.
- List Dataset Items
List items in a dataset.
- List Datasets
List all datasets in the project.
- List Prompts
List all prompts in the project.
- List Scores
List scores with optional filters.
- List Traces
List traces with optional filters (user, session, tags, timerange).
- Job completed
Fires when a job finishes (success/failure). Backed by the vendor's webhook endpoint delivery mechanism, filtered to job-completion events.
- Add asset
Initialize an asset (media file) upload.
- Add job
Create a media processing job (transcode, caption, watermark, etc).
- Cancel job
Cancel a running job.
- Delete asset
Delete an asset by id.
- Get asset
Get details of an asset by id.
- Get job
Get details of a job by id.
- Get job logs
Get execution logs for a job.
- Get job output
Get the download URL/content for a completed job's output.
- List assets
List uploaded assets.
- List jobs
List jobs for the account.
- List job types
List available job types (transcode, caption, watermark, etc).
- List models
List available generation/processing models.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
What our customers say
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Questions
Langfuse and Rendobar, answered
How does the agent know which Langfuse trace a Rendobar job belongs to?
Carry the trace id in the job metadata when the Rendobar job is created, then read it back on the Job completed trigger. The agent uses it to target Add Score, Add Comment or Get Trace in Langfuse, and tests every scenario before it runs on live jobs.
Can a failed Rendobar job be handled differently from a successful one?
Yes. The Job completed trigger fires for both success and failure, so the agent can check the result and only add a Langfuse dataset item or score when the job succeeded, while a failure gets a comment on the trace instead.
What can start an automation from Langfuse?
Any of Langfuse's 1 trigger in the catalog, including New Trace. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Rendobar when something happens in Langfuse?
Any of Rendobar's 12 actions, including Add asset, Add job, Get job output and Get asset. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Rendobar to Langfuse?
Yes. When something happens in Rendobar, your agent can act in Langfuse too. This page covers both directions: Rendobar's triggers and Langfuse's actions are listed here as well.
Do I have to build a connector for Langfuse or Rendobar?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
Can my AI client use Langfuse and Rendobar without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.