Integration
Connect Langfuse and Snowflake
When New Trace fires in Langfuse, your agent runs Create Rows in Snowflake, or New Column in Snowflake 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 Snowflake 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)Example flows
What Langfuse and Snowflake can do together
From Langfuse to Snowflake
When New Trace in Langfuse
then Create Rows in Snowflake
From Snowflake 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 Snowflake
Triggers and actions 6 triggers · 19 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).
- New Column
Triggers when a new column is added to a table in the chosen Snowflake database, optionally limited to one schema or table.
- New or Updated Row
Triggers when a row is added to or changed in a Snowflake table, checking the most recently updated rows by a timestamp column you choose.
- New Row
Triggers when a new row is added to a Snowflake table.
- New Table
Triggers when a new table is created in a Snowflake database.
- New View
Triggers when a new view is created in the selected Snowflake database (optionally limited to one schema).
- Create Rows
Inserts one or more rows into a Snowflake table.
- Delete Rows
Deletes every row in a Snowflake table whose chosen column equals the value you supply.
- Execute SQL
Runs a SQL statement in Snowflake and returns its result rows and column metadata.
- Find Row
Finds the first row in a Snowflake table whose chosen column equals a given value and returns its column values.
- Update Rows
Updates a column's value on every row in a Snowflake table whose match column equals the given value.
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 Snowflake, answered
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 Snowflake when something happens in Langfuse?
Any of Snowflake's 5 actions, including Create Rows, Update Rows, Execute SQL and Find Row. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Snowflake to Langfuse?
Yes. When something happens in Snowflake, your agent can act in Langfuse too. This page covers both directions: Snowflake's triggers and Langfuse's actions are listed here as well.
Do I have to build a connector for Langfuse or Snowflake?
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 Snowflake 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.