Bagel
MCP Server
Product Decisions Your Agents
Can Build On
The Bagel MCP gives Claude Code, Claude Co-work, Cursor, Codex or any other AI agent the customer evidence, revenue context, and scoped decisions behind every build, so your agents query, reason over, and build against real customer use cases on demand.
Inside the Bagel MCP
Scoped decisions, ready to build
Your agents pull who asked for a feature, the ARR at stake, and roadmap position. Every answer links to the calls, tickets, and records behind it.
One source, every build
Your team and your AI agents read the same customer evidence, revenue context, and scoped decisions from one place.
Works with the tools you run
Claude Code, Cursor, Codex, and any MCP client connect in minutes. No custom integration work.
Give every agent the customer context it’s missing.
Without customer context, speed just ships the wrong feature sooner. The Bagel MCP scopes the decision before your agents touch the code.
Every Signal, Scoped into Decisions Your AI Agents Can Build On
Your customer signal lives in twenty different places. Bagel does the triage, the prioritization, and the scoping behind every decision, then serves the finished evidence through MCP to Claude Code, Cursor, Codex, and any AI client on your stack.
Every tool. Every signal. One decision layer.
Your customer signal lives across sales calls, support tickets, and CRM notes, plus over 100 other sources. Bagel reads from every one, triages the noise, quantifies the impact, and organizes it into scoped decisions. Your agents query one source instead of fifty.
See Bagel AI In Action!
Pick a time. We’ll show you what the autonomous decision layer looks like with your data behind it.
Some good words from our customers
Your data is safe with us
Bagel AI ensures top-tier security and compliance, protecting your feedback, roadmaps, and outcomes while seamlessly integrating with your tools. Focus on impact with confidence.
FAQ
The Bagel MCP is a server that exposes your customer evidence, revenue context, and scoped product decisions to any AI client that speaks the Model Context Protocol. Your agents query it the same way they query a codebase, and get decision-level answers back.
Scoped decisions. Ask which customers requested a feature and you get the list ranked by ARR, the roadmap position, and a link to the calls and tickets behind it. Your agents build against the answer.
Sales calls, support tickets, CRM notes, and over 100 other sources across your GTM stack, including Gong, Salesforce, Zendesk, Slack, and Jira. Bagel reads from all of it, triages the noise, quantifies the impact, and organizes it into scoped decisions.
Point an agent at raw Salesforce and it gets a warehouse of unsorted records. The Bagel MCP serves the decision with the evidence attached, so your agent reads who asked, what it is worth, and where it sits. Less prompting, fewer hallucinations, better first-pass output.
You can. Spinning one up for a single source takes an afternoon. Building one that synthesizes Gong, Salesforce, Zendesk, Slack, and Jira into decision-level outputs takes months, plus ongoing maintenance. Bagel ships that server out of the box.
Both. Any team running AI agents against a product roadmap benefits from feeding those agents real customer context. The size of your stack changes how much signal Bagel synthesizes, not whether the MCP helps.
Contact us at sales@getbagel.com or book a demo.