Pensero MCP — Your engineering intelligence, now queryable[Skip to content](#main) [Pensero](/) - Platform Measure - [Agentic ROICost per unit of delivered work](/platform/agentic-roi) - [AI DeploymentAdoption, output and quality of AI](/platform/ai-intelligence) - [Delivery IntelligenceOutput and flow by source](/platform/delivery-intelligence) Govern - [BenchmarkingCompare agents, models and humans](/platform/talent-benchmarking) - [Code QualityDefects and rework by source](/platform/code-quality) - [CapEx & FinanceCapitalization and spend allocation](/platform/capex-analysis) [Pensero MCPNewQuery your data from any assistant](/platform/mcp) - Use cases By role - [CEOs](/use-cases/roles-ceo) - [CTOs](/use-cases/roles-cto) - [CFOs](/use-cases/roles-cfo) - [Product leaders](/use-cases/roles-product-leaders) - [Engineering managers](/use-cases/roles-engineering-managers) - [Investors](/use-cases/roles-investors) Compare Pensero - [DX](/use-cases/competitors-dx) - [Swarmia](/use-cases/competitors-swarmia) - [Haystack](/use-cases/competitors-haystack) - [Span](/use-cases/competitors-span) - [Jellyfish](/use-cases/competitors-jellyfish) - [Waydev](/use-cases/competitors-waydev) - [LinearB](/use-cases/competitors-linearb) - [Faros AI](/use-cases/competitors-farosai) - [Sleuth](/use-cases/competitors-sleuth) - [Larridin](/use-cases/competitors-larridin) - [Weave](/use-cases/competitors-weave) - [Exceeds AI](/use-cases/competitors-exceeds-ai) - [GitHub Copilot](/use-cases/competitors-github-copilot) - [Customers](/customers) - [Sources](/integrations) - [Pricing](/#pricing) - Resources - [BlogNews, tips, and dev culture](/blog) - [ROI CalculatorEstimate your cost savings](/landing/roicalculator) [Log in](/auth/login/)[Book a demo](/book-demo) [Log in](/auth/login/)[Book a demo](/book-demo) Pensero MCP # Engineering intelligence, now queryable. Query your live Pensero data straight from Claude, ChatGPT or any MCP-compatible assistant. Ask about delivery, quality, AI adoption or benchmarks in plain language. [Book a demo](/book-demo) Pensero MCPsummarize_quarter What should I highlight in my board update? Claude ## Works with the assistants your team already uses - Claude - OpenAI - Gemini - GitHub Copilot ## Ask it the way you’d ask your best analyst Plain questions in, answers grounded in your own data out, then keep pulling the thread with follow-ups. - How did engineering perform this quarter? - Where is AI creating measurable impact? - Which teams are improving fastest? - What should I highlight in my board update? - How do we compare against benchmark companies? - Which engineering investments are delivering the highest ROI? ## Why Pensero MCP Four things that separate an answer from Pensero MCP from an answer a general-purpose assistant guesses at. 01 — Source of truth ### Built on your engineering source of truth Every answer is generated from your live Pensero data, the same unified model behind your dashboards. No exports, no stale spreadsheets, no numbers that disagree with the ones your team already reviewed. - Live data - One unified model - No exports Total DeliveryTotal points delivered29.9kpts12% Weekly Delivery Per PersonAverage weekly delivery per active contributor58.3pts9% AI-written codeShare of merged code that was AI-written64%18% Cost per pointAI spend per delivery point among active contributors$1.128% Defect cost %Share of delivery spent fixing bugs9%6% Roadmap AlignmentShare of delivery aligned with roadmap68%7% Collaboration RatioShare of delivery spent collaborating21%4% Issue Cycle Time (P90)P90 time from ticket assignment to PR merge96.4hrs12% Total DeliveryTotal points delivered29.9kpts12% Weekly Delivery Per PersonAverage weekly delivery per active contributor58.3pts9% AI-written codeShare of merged code that was AI-written64%18% Cost per pointAI spend per delivery point among active contributors$1.128% Defect cost %Share of delivery spent fixing bugs9%6% Roadmap AlignmentShare of delivery aligned with roadmap68%7% Collaboration RatioShare of delivery spent collaborating21%4% Issue Cycle Time (P90)P90 time from ticket assignment to PR merge96.4hrs12% Pensero MCPLive connection to Claudeconnected 02 — Conversation ### Natural conversations, not report requests Start broad, then drill in. Ask why a number moved, which team it came from and what changed since last month, without leaving the assistant you already have open. - Follow-up questions - Anomaly investigation - Trend exploration What should I highlight in my board update? Comparing delivery since January Lead with delivery. Delivery points per person are up 28% since January. The whole curve moved, so it’s the whole team, not a few people. Jan – Feb · mean 244Jun – Jul · mean 312 0200400600 Delivery points per person, monthly Mean **244 → 312**Change **+28%**Spread **flat** Which teams drove it? Ranking teams by change Biggest movers since January Platform 18 people+41% Payments 11 people+33% Mobile 9 people+24% Pensero MCPconnected Claude 03 — Compatibility ### Works with the tools you already run Pensero exposes a standard MCP server, so it connects to Claude, ChatGPT and any MCP-enabled assistant. Nothing new for your team to learn, no extra tab to keep open. - Claude - ChatGPT - Any MCP client 04 — Security ### Enterprise-ready by default MCP uses your existing Pensero authentication and permissions. Every request is scoped to the person asking, so nobody can reach data they couldn’t already see in Pensero. - Existing authentication - Permission-scoped - No new access surface ![SEAT CODE](/assets/seat-code.Y7Tj-94e.svg) > "It's important that we select the right information at the right moment, based on the maturity and the knowledge that we have on the platform." ![](/assets/jordi-abad.BHIFVIdm_2nkKgW.webp)Jordi AbadCTO, SEAT CODE [Read story →](/customers/seatcode)![Stord](/assets/stord.BXJiX-0z.svg) > "I can go to Pensero and tie all this together in a great format." ![](/assets/nick-traylor.C0_VmQDQ_1MV60T.webp)Nick TraylorHead of Engineering, Stord [Read story →](/customers/stord) ## Questions teams ask about MCP Which assistants does it work with? Any MCP-compatible assistant, including Claude and ChatGPT. If your assistant speaks MCP, it can connect to Pensero. Who can see what? Every request runs under the identity of the person asking, using your existing Pensero authentication and permissions. Nobody can reach data through MCP that they could not already see in Pensero. Is the data live? Yes. Answers are generated from your live Pensero data at the moment you ask — not from a snapshot, an export or a cached report. ## More on Pensero's platform - [Agentic ROI →Measure the return on agentic AI spend.](/platform/agentic-roi) - [AI Deployment →Understand the true impact of AI on engineering performance.](/platform/ai-intelligence) - [Delivery Intelligence →See how work actually moves across teams and tools.](/platform/delivery-intelligence) - [Talent & Benchmarking →Benchmark and calibrate engineering performance fairly.](/platform/talent-benchmarking) - [Code Quality →Track maintainability, defects, and rework over time.](/platform/code-quality) ## Get months of engineering performance data now Stop deciding on gut feel. Get 90 days of objective data in minutes. 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