🥯 Bagel MCP: Give Claude, Cursor, and Codex evidence-backed product decisions to build on

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.

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Jira
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Zendesk
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AI-driven teams make better decisions with Bagel AI
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hivebrite
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Inside the Bagel MCP

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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.

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One source, every build

Your team and your AI agents read the same customer evidence, revenue context, and scoped decisions from one place.

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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.

Agents without customer context
Your coding agent ships fast and ships blind.
Agents on the Bagel MCP
Claude Code, Cursor, and Codex read customer context through MCP before they write a line.
Agents without customer context
Every agent guesses the spec from a ticket title.
Agents on the Bagel MCP
Customer signal arrives as a scoped decision your agents can build against.
Agents without customer context
Roadmaps, PRDs, and tickets pull from different or non-existent context.
Agents on the Bagel MCP
One layer underneath every artifact. Same context, same evidence, same call.
Agents without customer context
Engineers ship the wrong thing faster than ever.
Agents on the Bagel MCP
Product pains and gaps extracted from any feedback source, ready to query.
Agents without customer context
No way to tell whether the AI-built feature mattered.
Agents on the Bagel MCP
Every shipped decision measured against the customer outcome it was built for.
Agents without customer context
Your stack is token-maxxing. Burning compute, racking up bills, looking AI-native.
Agents on the Bagel MCP
Bagel is impact-maxxing. Every signal your agents process leads to a scoped decision and a measurable outcome.
One MCP, every agent

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.

Speaks MCP to:
Claude Code
Codex
Cursor
Any AI client
Sources

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

“Bagel AI helps us uncover blind spotsblind spots bringing evidence from different channels (sales calls, support teams etc.) making our product decisions sharper and more aligned with growth.”

Tarek
Tarek Kamoun
CPTO, Hivebrite

“Bagel AI has been a crucial tool for us in turning GTM team feedbackturning GTM team feedback into quantifiable insights. It provides clear evidence to justify investment in new features, ensuring we make informed, high-impact product decisions.”

Ido Ivri
Ido Ivry
Co-Founder & CTO, Zencity

“Bagel AI is unmatched in the industry! The bespoke model built for HoneyBook helped us prioritize the most impactful featuresprioritize the most impactful features cutting through the noise of our large user base. Highly recommended!”

Daniel Benor
Daniel Benor
Head of Product Innovation, Honeybook

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.

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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.

Book a Demo