Integration
Connect Bitbucket to Infranodus
When New pull request fires in Bitbucket, your agent runs Compare graphs in Infranodus. 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 Bitbucket and Infranodus 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 Bitbucket can start in Infranodus
When New pull request in Bitbucket
then Compare graphs in Infranodus
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 Bitbucket and Infranodus
Triggers and actions 1 trigger · 17 actions
- New pull request
- Add branch
/2.0/repositories/{workspace}/{repo_slug}/refs/branches
- Add pull request
/2.0/repositories/{workspace}/{repo_slug}/pullrequests
- Add pull request comment
/2.0/repositories/{workspace}/{repo_slug}/pullrequests/{id}/comments
- Add repository
/2.0/repositories/{workspace}/{repo_slug}
- Get pull request
/2.0/repositories/{workspace}/{repo_slug}/pullrequests/{id}
- List branches
/2.0/repositories/{workspace}/{repo_slug}/refs/branches
- List pull requests
/2.0/repositories/{workspace}/{repo_slug}/pullrequests
- List repositories
/2.0/repositories/{workspace}
- Update pull request
/2.0/repositories/{workspace}/{repo_slug}/pullrequests/{id}
- Compare graphs
Builds knowledge graphs from two or more texts and compares them, returning the merged, overlapping (intersection) or differing concepts, topics and gaps.
- Find statements
Searches your InfraNodus graphs for statements that contain a word or concept, and returns the matching statements.
- Generate advice from graph
Analyzes one of your saved InfraNodus graphs and returns AI-generated advice, such as ideas, questions or responses that bridge the content gaps between its topics.
- Generate advice from text
Analyzes a piece of text as a knowledge graph and returns AI-generated advice, ideas or research questions based on the content gaps between its main topics.
- Generate graph from Google search results
Builds a knowledge graph of the main topics, clusters and content gaps found in the Google search results for one or more search queries.
- Generate graph from search intent
Builds a knowledge graph of the Google searches people make around your queries, showing the main topical clusters and gaps in search intent.
- Generate graph from text
Builds a knowledge graph from a text, returning its topical clusters, content gaps, main concepts and network statistics. Optionally saves the graph to your InfraNodus account.
- List graphs
Returns the knowledge graphs in your InfraNodus account, optionally filtered by name, graph type, creation date, language or favorite status.
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
Bitbucket and Infranodus, answered
What can start an automation from Bitbucket?
Any of Bitbucket's 1 trigger in the catalog, including New pull request. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Infranodus when something happens in Bitbucket?
Any of Infranodus's 8 actions, including Compare graphs, Find statements, Generate advice from graph and Generate advice from text. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Infranodus to Bitbucket?
Infranodus has no triggers in the catalog today, so automations start in Bitbucket. If you need the other direction, ask: your agent reads Infranodus's API documentation and adds it.
Do I have to build a connector for Bitbucket or Infranodus?
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 Bitbucket and Infranodus 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.