AI & Machine Learning · Braintrust + Claude
Braintrust MCP with Claude: Faster AI Evaluations and Debugging
The short answer
Claude works with Braintrust through the Model Context Protocol, a secure standard that lets Claude read and act inside the tool with permissions you set. Once connected, teams can manage prompts, inspect experiments, query evaluations and review production traces by asking questions in plain English, with people approving important changes.
What is Braintrust?
Braintrust is an AI engineering platform used by teams that build AI systems and chatbots. It brings together prompts, datasets, experiments, evaluations, observability and production monitoring in one place. Engineers, product managers and AI quality teams use it to test changes before release, understand why an AI answer went wrong, and track quality over time. It helps teams ship AI features with clearer evidence and faster feedback loops.
How Claude connects to Braintrust through MCP
The Model Context Protocol, or MCP, is an open standard that acts like a universal adapter between Claude and other software. It lets Claude use a tool securely, reading information and taking actions, with access that your organisation decides and can withdraw at any time.
Once Braintrust is connected, Claude can read prompts, datasets, experiments and evaluation results, and help you summarise them. It can also review production traces to explain where an AI response went wrong. Where your setup allows, it can draft prompt changes or prepare new evaluation runs for your team to check.
Permissions and approvals keep people in charge. Access is limited to the projects and actions you approve, and sign-in uses a Braintrust API key held in a secure store. Consequential changes, such as publishing a new prompt to production, pass through a human approval step. Audit logs record what Claude did, so every action can be traced.
What you can automate
Weekly quality summaries for AI product teams
Claude reads recent experiment and evaluation results and produces a plain-English summary of what improved, what regressed and which test cases need attention. Product managers get a clear picture without learning the tool, and engineers spend less time compiling reports by hand.
Investigating chatbot complaints
When customers report a poor answer from a support chatbot, Claude can search production traces for similar conversations, identify the prompt version involved and explain the likely cause. This shortens the time from complaint to fix and gives support leads a clear account of what happened.
Comparing prompt versions before release
Before a prompt change goes live, Claude can compare evaluation scores across versions and highlight the test cases where results differ. Teams can make release decisions based on evidence rather than intuition, and document the reasoning for later review.
Building and maintaining evaluation datasets
Claude can help review examples in a dataset, suggest gaps such as missing edge cases, and draft new test entries for approval. Subject-matter experts keep control of what counts as a correct answer, while the team builds a stronger test set over time.
Tracking cost and latency for leadership
Claude can pull trace and experiment data to show trends in response time and usage across AI features. Operations and finance leads receive simple, regular updates that support budget decisions for AI systems.
An end-to-end workflow: Chatbot quality review with ticket follow-up
TriggerEvery Monday at 08:00, or when a support lead flags a batch of poor chatbot answers.
Claude pulls the week's production traces for the customer support chatbot from Braintrust.
It groups low-rated or flagged conversations by topic and identifies the prompt version used.
Claude drafts a short report of recurring failure patterns with example conversations.
The AI quality lead reviews and approves the report before anything is shared.
Approved findings are logged as tickets in the team's ticketing system, linked to the relevant prompt and evaluation run.
Claude tracks the tickets and adds the next evaluation results to the same record once a fix is tested.
OutcomeRecurring chatbot problems are found and assigned within days instead of weeks, with a traceable record linking each fix to its evidence. Typical teams report faster, more consistent quality reviews, though results vary by organisation.
How we set it up
Free automation audit
We review how your AI teams currently test, debug and release prompts and chatbots, and identify the workflows where Claude and Braintrust would save the most time.
Secure connection
We connect Claude to Braintrust using a Braintrust API key stored in a secure secrets manager, with least-privilege access limited to the projects you approve.
Workflow design
We design the end-to-end process across Braintrust and your other systems, such as Microsoft 365, your CRM or ticketing tool, and define which actions need human approval.
Testing and launch
We test the workflow against real past cases, then launch with monitoring and audit logs turned on so every action can be reviewed.
Team training
We train your engineers, product managers and quality leads on how to use Claude with Braintrust safely, and document the approval steps for ongoing use.
Who benefits
- AI and engineering leads
- Faster debugging of prompts and chatbot failures, with clearer evidence behind each release decision.
- Product managers
- Plain-English summaries of experiment results, without needing to learn the tool in depth.
- Customer support and operations heads
- Quicker routes from customer complaints to root causes and tracked fixes.
- Finance and business leaders
- Regular, understandable updates on AI quality, usage and cost trends.
Security and control
- Access is limited to the Braintrust projects and actions you approve, using a dedicated API key.
- Consequential changes, such as publishing prompts to production, require a named person's approval.
- Audit logs record each action Claude takes in the connected workflow.
- API keys are stored in a secure secrets manager and rotated on a regular schedule.
- Data handling follows your own policies, and we confirm this during the audit before any connection is made.
For teams in the US, UK, India and the Middle East
Organisations in the United States and the United Kingdom can host the Claude workflow in their chosen region to meet their own data handling requirements. Companies in India must consider the Digital Personal Data Protection Act, 2023, and we design India-hosted options where needed. Organisations in the UAE and Saudi Arabia must follow local data protection laws, and we can host Claude in a region that supports those requirements. The hosting region is always chosen to meet the requirements of each client.
Learn more about Claude and MCP
Anthropic's AI model and assistant.
Secure links between Claude and business tools.
How engineers build and change software with Claude.
Hosted agents that run multi-step work.
The open standard Claude uses to connect to tools.
Frequently asked questions
What does the Braintrust MCP server do?
The Braintrust MCP server acts as a secure bridge between Claude and your Braintrust account. It lets Claude read prompts, datasets, experiments, evaluations and production traces, and take the actions you permit. Access is controlled by the permissions you set, so Claude only sees and changes what your team has approved.
Is connecting Claude to Braintrust secure?
Security depends on how the connection is set up. We use a Braintrust API key stored in a secure secrets manager, limit access to approved projects, require human approval for consequential changes and keep audit logs of every action. We also confirm your data handling policies before connecting anything.
What can Claude do with Braintrust once it is connected?
Typically, Claude can summarise experiment results, compare prompt versions, query evaluation scores, search production traces for failure patterns and help draft dataset updates. Anything that changes live systems goes through an approval step first. The exact capabilities depend on the permissions your team grants.
How long does setup take?
Timelines vary with the number of projects, the systems involved and how many workflows are in scope. A focused connection with one workflow is often ready within a few weeks, including testing and team training. We confirm a realistic timeline during the free automation audit.
What Braintrust plan or permissions are needed?
Connecting Claude requires a Braintrust API key with access to the projects you want included. The exact account type and permissions depend on your Braintrust setup, so we check these during the free automation audit and recommend the least access needed for your workflows.