Integration
Connect Langfuse to WaniKani
When something happens in Langfuse, your agent does the next thing in WaniKani. Describe it 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 WaniKani to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiAny 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 can start in WaniKani
When New Trace in Langfuse
then Add review in WaniKani
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 WaniKani
Triggers and actions 1 trigger · 23 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.
- Add review
Records a completed review for an assignment (or subject), updating the assignment's SRS stage and its review statistic.
- Add study material
Create a study material (user's custom meaning/reading notes and synonyms) for a subject.
- Find assignments
Returns the user's assignments (their progress on each subject) that match the specified filters, up to 500 per call.
- Find subjects
Returns up to 1,000 WaniKani subjects (radicals, kanji, vocabulary, kana vocabulary) that match the specified ids, types, slugs, levels, hidden state or update time.
- Get study material
Fetches a study material by ID: the subject it belongs to, your meaning and reading notes, and your extra accepted meanings. An error occurs if the study material is not found.
- Get summary
Retrieves the summary report of lessons available now and reviews available now and over the next 24 hours, grouped by the hour.
- Get user
Returns the profile, level, subscription and preferences of the WaniKani user who owns the connected API token.
- Start assignment
Marks a WaniKani assignment as started, moving it from the lessons queue to the review queue, and returns the updated assignment.
- Update study material
Update an existing study material's notes/synonyms.
- Update user
Updates the WaniKani preferences of the user who owns the connected API token. Only preferences can be changed; fields left blank keep their current 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 WaniKani, 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 WaniKani when something happens in Langfuse?
Any of WaniKani's 10 actions, including Update study material, Update user, Add review and Add study material. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from WaniKani to Langfuse?
WaniKani has no triggers in the catalog today, so automations start in Langfuse. If you need the other direction, ask: your agent reads WaniKani's API documentation and adds it.
Do I have to build a connector for Langfuse or WaniKani?
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.
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.