Buildkite MCP. Manage CI/CD builds and agents via chat.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Buildkite MCP Server automates your CI/CD workflow. It lets you manage pipelines, trigger builds, and inspect logs directly through your AI client.
Use `list_pipelines` to see all active pipelines, `create_build` to launch tests, and `get_build` to pull specific build details. It gives you full control over builds and agents without opening a terminal or web console.
What your AI agents can do
Cancel build
Stops a running build immediately using its ID.
Create build
Initiates a new build run for a specified pipeline.
Get access token info
Retrieves details about the current Buildkite API token's status.
Trigger new builds, retry failed runs, or cancel running pipelines directly via the AI client.
Retrieve detailed build information, including job status and tracking links, for any given build ID.
List all connected build agents across your organization and check their current operational status.
View all defined pipelines within your organization and retrieve build history for a specific pipeline.
List all organizations the API token has access to, giving a full view of multi-tenant deployments.
Ask AI about this MCP
Supported MCP Clients
Gemini Waiting for input…
Buildkite MCP Server: 11 Tools for CI/CD Control
These tools let your AI agent interact with Buildkite to manage pipelines, agents, and build runs. You can trigger, inspect, and control every step of your deployment process.
019d7565cancel build
Stops a running build immediately using its ID.
019d7565create build
Initiates a new build run for a specified pipeline.
019d7565get access token info
Retrieves details about the current Buildkite API token's status.
019d7565get build
Fetches the detailed status and logs for a specific build run.
019d7565get pipeline
Gets the metadata and current status for a defined pipeline.
019d7565list agents
Lists all connected build agents across the entire organization.
019d7565list all builds
Retrieves a list of every build run across all pipelines in the organization.
019d7565list organizations
Shows all Buildkite organizations the API token can access.
019d7565list pipeline builds
Lists all historical build runs associated with a specific pipeline.
019d7565list pipelines
Shows every pipeline defined within the current organization.
019d7565rebuild
Forces a rerun of a specific, completed build.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Buildkite, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Buildkite MCP Server gives your AI client full control over your CI/CD workflow. You'll manage pipelines, trigger builds, and check logs right through your agent, skipping the terminal or web console. You can use list_pipelines to see every pipeline defined in your organization, and list_all_builds to get a complete rundown of every build run across the entire company.
You'll also find a way to get_pipeline to check the metadata and current status of a specific pipeline. To start tests, use create_build to initiate a new build run for any specified pipeline, and you can use rebuild to force a rerun of a finished build. You can use get_build to fetch the detailed status and logs for any given build run.
If a build gets stuck, you can use cancel_build to stop it immediately using its ID. To see all connected build agents, run list_agents to get a list of every agent across your organization. You can use list_organizations to show all Buildkite organizations the API token can access, which is useful for multi-tenant setups.
You can view all historical build runs for a specific pipeline using list_pipeline_builds. To check the credentials, run get_access_token_info to retrieve details about the current Buildkite API token's status. You'll also have a way to view all Buildkite organizations the API token can access by calling list_organizations.
How Buildkite MCP Works
- 1 Subscribe to the Buildkite server and input your Buildkite API Token and Organization Slug.
- 2 Ask your AI client to perform a build action (e.g., 'Trigger a build on the main branch').
- 3 The agent calls the appropriate tool (e.g.,
create_build), executes the action, and returns the status and results to you.
The bottom line is, your AI agent handles the API calls, so you don't have to remember the specific buildkite command structure.
Who Is Buildkite MCP For?
The DevOps engineer tired of clicking through dashboards at 2 am. This server is for platform teams and senior software engineers who need visibility and control over complex, multi-stage deployments. It lets you manage infrastructure state and pipeline health without leaving your IDE or chat window.
Orchestrates hybrid CI infrastructure, monitors hanging processes, and cancels stuck builds without manual console access.
Manages build agents globally, verifies their status, and tracks active pipelines across multiple client organizations.
Triggers ad-hoc test runs on specific feature branches or branches for code review without breaking flow in their IDE.
What Changes When You Connect
- Run ad-hoc tests instantly: Use
create_buildto trigger a build on a feature branch without leaving your IDE. This cuts out the steps of switching to the Buildkite UI just to test a merge. - Get full build context: Need to know why build #205 failed?
get_buildprovides the exact details, job lists, and status tracking links immediately. - Track everything globally:
list_all_buildslets you see every build run across the entire company, which is crucial for auditing compliance or finding a specific historical deployment. - Control the environment: If a build gets stuck or runs with bad commits, use
cancel_buildto halt it immediately. This saves compute time and prevents bad code from proceeding. - See the infrastructure status:
list_agentslets you verify if your build agents are online and ready to run jobs. This is a quick check before committing to a deployment. - Audit organization scope:
list_organizationsshows all accounts linked to your token. This is vital when managing multi-tenant or multi-department CI/CD infrastructure.
Real-World Use Cases
Debugging a failing microservice deployment
A developer pushes a change, but the deployment fails. Instead of navigating to the Buildkite dashboard, they ask their agent: 'What went wrong with the last build for the payment service?' The agent uses get_build and list_pipeline_builds to retrieve the failure details, pointing directly to the failing job step. The problem is solved in the chat window.
Running pre-merge smoke tests
A tech lead wants to confirm a feature branch is stable before merging. They prompt their agent: 'Trigger a build for the new API gateway feature branch.' The agent calls create_build, and the tech lead monitors the status without leaving their code review session.
Cleaning up runaway builds
An engineer commits a bad commit that starts a massive, multi-stage build. They immediately prompt the agent: 'Cancel the build for the core service.' The agent calls cancel_build, halting the process and saving compute resources.
Verifying agent readiness for a release
The Ops team needs to ensure all deployment agents are online before a major release window. They ask the agent to run list_agents. The agent replies with a clean list of agent IDs and their active status, confirming the environment is ready.
The Tradeoffs
Sequential Build Status Checks
Trying to manually check build status by running list_pipelines to get IDs, then calling get_pipeline for each ID, and finally calling list_pipeline_builds for every single one. This is a massive, slow, multi-step process that requires constant context switching.
→
To get a comprehensive status overview, start by asking your agent to run list_all_builds. This aggregates the data you need in a single call, reducing round trips and providing a quick overview of all recent activity.
Assuming the Build Status is Always Current
Relying on stale information from a local build status or a non-updated dashboard widget. This leads to wasting time waiting for a job that has already failed or finished.
→
Always verify the current state using get_build. This tool fetches the real-time, detailed status of a specific build run, giving you the truth source.
Overlooking Organizational Scope
Only checking build status within one project's scope, missing critical failures in a different, dependent service or organization.
→
Use list_organizations first to map all available accounts. Then, use list_all_builds to pull aggregated status reports across your entire infrastructure.
When It Fits, When It Doesn't
Use this server if your job requires tracking build state across multiple services, organizations, or time periods. You need the ability to trigger builds and immediately inspect logs without leaving your current terminal or IDE. The best use case is debugging complex, multi-service deployments where speed matters.
Don't use this if you only need to manage a single, isolated build process, or if you are building a custom UI that already has direct, stable API access to every endpoint. If you already have that, the overhead of passing credentials to an agent might be overkill. For simple, single-pipeline status checks, querying the get_pipeline tool is usually sufficient, but for full lifecycle management, this server is necessary.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Buildkite. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 11 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Jumping between the terminal, the web UI, and the IDE to check build status is a nightmare.
Today, checking a build status means jumping through hoops. You run `list_pipelines` in the terminal, copy the ID, paste it into the web UI, navigate to the specific build, and then hunt through logs. If the build fails, you copy the error code and paste it into a chat to ask a teammate. It's a total workflow killer.
With the Buildkite MCP Server, you tell your agent what you need. You ask, 'What's the status of the main branch build?' and the agent runs `list_all_builds` and `get_build` for you. You get the status and the necessary logs right in the chat. No tabs, no copies, no switching.
Buildkite MCP Server: Control your entire deployment cycle.
You don't just check status; you actively control the flow. You can use `create_build` to run a smoke test or `cancel_build` to kill a runaway job. You can even use `rebuild` if the initial run was bad. These are actions, not just reads.
The shift is moving build operations from being a series of sequential, manual API calls to being a single, conversational instruction. Your agent becomes the operational command center.
Common Questions About Buildkite MCP
How do I check all builds across different departments using the Buildkite MCP Server? +
Use list_organizations first to see all accessible accounts. Then, run list_all_builds to pull an aggregated report covering builds across your entire infrastructure.
Can I trigger a test run using the Buildkite MCP Server? +
Yes, you use the create_build tool. You just need to specify the target pipeline or branch, and the server launches the job.
Is `get_build` the right tool to debug a failing deployment? +
Yes, get_build is the primary tool. It retrieves detailed status, job lists, and tracking links for a specific build ID, which is exactly what you need for debugging.
What if I need to force a build to run again? +
You use the rebuild tool. It forces a rerun of a specific, previously completed build, which is useful if you suspect the initial run had transient network issues.
How do I check the status of connected build agents using the `list_agents` tool? +
The list_agents tool gives you a real-time overview of every build agent. It reports their current status, letting you verify if they're online and ready to run jobs.
What if I need to get the detailed history of a specific pipeline using `get_pipeline`? +
The get_pipeline tool retrieves all the configuration details for a given pipeline. You can see its history, which is key for understanding how the pipeline structure has changed over time.
Can I list all the builds that ran for a single pipeline using `list_pipeline_builds`? +
Yes, list_pipeline_builds is exactly for that. It provides a dedicated list of every build associated with one specific pipeline ID, keeping your history organized.
What is the purpose of the `get_access_token_info` tool? +
This tool confirms your API token's validity and scope. It shows you details about the token itself, which is useful for debugging authentication issues or checking permissions.
Can my AI agent restart failed builds for a specific branch? +
Yes. Ask the agent to find failed builds across your pipeline by using the list builds tool. Once it locates the specific build number, it can run the rebuild tool instantly, eliminating the need to search through hundreds of logs on the dashboard.
How can I check the status of my physical runner agents? +
Ask your agent to list all agents connected to the Buildkite organization. It returns their UUIDs, operating systems, and connection state. If a runner hangs offline, your AI can immediately flag it to the Platform team, saving crucial deployment time.
If a commit is pushed to 'main', can the agent trigger a fresh pipeline deployment? +
Absolutely. You can provide the commit SHA (or simply ask it to target 'HEAD' on the 'main' branch) and ask the agent to create a new build. It will hit the Buildkite trigger endpoint with a message of your choosing.
Multi-server workflows that include Buildkite MCP
Debug CI Pipeline Failures Faster Using MCP
Your CI pipeline takes 47 minutes and nobody knows which step is the bottleneck , your AI agent analyzes every build, identifies the slow steps, and posts a weekly efficiency report
MCP Workflow for Automated Release Notes
PRs merged, builds validated, changelogs written, release pages published , generate polished release notes without copy-pasting commits
MCP Workflow for Container Build Monitoring
Pipelines monitored, build times tracked, image sizes audited, flaky steps flagged , keep your CI healthy without watching build logs
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
More in this category
Drupal
Manage headless content via Drupal — list nodes, handle taxonomy terms, manage files, and audit users directly from any AI agent.
Bitbucket
Manage your Git repositories via Bitbucket — list pull requests, commits, and pipelines directly from any AI agent.
Fastly
Manage edge computing and CDN via Fastly — monitor and activate service versions, manage domains and backends, and purge cache directly from any AI agent.
You might also like
LibreTranslate API
Translate and detect text — audit languages via AI.
Semgrep
Equip your AI agent with read/write access to Semgrep's SAST platform to audit code security findings, update triage statuses, and enforce custom semantic rules.
Desku.io
Unify customer support across email, chat, and social with AI-assisted ticket resolution that speeds up response times.