GitRevio MCP Server for AI Intelligence and Engineering Data Platform
GitRevio connects your AI tools directly to engineering intelligence through a powerful engineering data platform. Access real-time insights, delivery analytics, team health metrics, and reports inside Claude, Cursor, Windsurf, ChatGPT, or any MCP client. Built on a modern developer analytics infrastructure, with no dashboard wrappers. Just real tools, real data, and real access control.
What Is GitRevio MCP Server?
GitRevio MCP Server is a secure Model Context Protocol (MCP) integration powered by an engineering data platform. It allows AI assistants to access real-time engineering insights, productivity metrics, delivery trends, onboarding signals, code quality data, and risk forecasts.
Instead of manually checking dashboards, leaders can ask:
All answers are generated from a structured developer analytics infrastructure, ensuring accuracy and traceability.
Try GitRevio MCPWhy Engineering Teams Need MCP-Based AI Tools
Most AI tools lack context. They write code, summarize text, or answer generic questions. GitRevio changes that by giving your AI tools a real engineering data platform:
Your AI becomes useful because it understands how your engineering org actually works.
Set up in 60 seconds
Access your engineering data platform instantly — one JSON block or one CLI command.
One JSON block or one CLI command. Your AI tool now has access to a full engineering data platform backed by GitRevio.
Works in 7 clients on day one: Claude Desktop, Claude Code, Cursor, Cline, Continue.dev, Goose, and Aider — plus ChatGPT via the MCP bridge. We ship setup guides for each one.
API key scoped to your role. ICs see me_*
tools. Team leads see team_*. CTOs see
exec_*. No shared-access loopholes.
Works With All Major AI Tools
Use one engineering data platform across every AI environment.
Secure Role-Based Access Controls
Every API key is scoped to permissions. Your AI only sees what the user is allowed to see — secured through a robust developer analytics infrastructure.
Four tool groups, structured outputs
Not a single "query" endpoint that returns raw text. Each tool is purpose-built, returns structured data, and can be composed by your AI agent.
50+ pre-built prompts for engineering leaders
Don't start from scratch. Our prompt library covers the most common engineering intelligence questions, tested and refined to produce reliable outputs. Every prompt is backed by real data from your engineering data platform.
Direct queries over canonical entities — repos, contributors, teams, PRs, issues, sprints, expertise, AI impact, review queues.
Every builtin skill is executable from MCP via gitrevio_skill_run. Custom skills installed by your org appear automatically.
One-call dashboards for each role. me_today for ICs, team_standup for EMs, exec_board_snapshot for CTOs.
Where most competitors stop. Your AI agent can act — schedule a report, register a webhook, install a skill, share a chat.
Persona-aware filtering
An IC's MCP surface is tactical: today, this week, this PR. A CTO's is strategic: the quarter, the org, the AI ROI. The server filters what's visible based on the API key's role — same protocol, five different surfaces.
| Persona | Primary questions | Tool surface | Horizon |
|---|---|---|---|
| IC (Engineer) | What should I review? Why is my PR stuck? Who should review this? | me_*, release-risk, optimal-reviewer | Day, week, sprint |
| EM | Who's stuck? At risk? Slipping? How's the sprint? | team_*, sprint-autopsy, plan-vs-reality, attrition-risk | Sprint, quarter |
| VP | Which teams are healthy? Cross-team bottlenecks? Hiring gaps? | portfolio_*, what-if, org-health, board-report | Quarter, half-year |
| CTO | Board-ready update? AI ROI? Plan adherence? Strategic risks? | exec_*, Shapley causal analysis, AI impact | Half-year, year, board cycle |
| CEO | Will engineering deliver the strategy? | company_engineering, exec-board-snapshot | Year, fundraise |
Five MCP resources
Beyond tools, the server exposes read-only resources your AI agent can fetch as context.
Audit-logged. Rate-limited. SHA-256-keyed.
Every tool call is logged. Hashed API key, tool name, parameters with PII redacted,
status, duration. Surfaced to your admin via GET /api/v1/audit/mcp.
Audit events also flow to a durable sink — SIEM export ships Q1 2027.
Rate-limited per session via token bucket. RPM is configurable per API key and visible in the dashboard. No surprise throttling, no opaque quotas.
API keys SHA-256 hashed at rest. Plain-text keys are shown once at creation and never recoverable — rotate, don't recover.
Why GitRevio is better than generic MCP servers
The gap isn't whether you have an MCP server — it's whether your AI agent can act through it.
| Gitrevio | LinearB | Swarmia | Others | |
|---|---|---|---|---|
| MCP tools | 136 (read + write + dashboards + skills) | ~10 read-only | ~20 read-only | None or read-only |
| Persona-aware filtering | 5 personas (IC, EM, VP, CTO, CEO) | — | — | — |
| Pre-built prompts | 50+ | ~10 | — | — |
| Write actions (alerts, reports, skills) | ✓ | — | — | — |
| Audit log of every tool call | ✓ (PII-redacted, SIEM export Q1 2027) | — | — | — |
| Custom skill execution | ✓ via `gitrevio_skill_run` | — | — | — |
| Distribution | npm + PyPI (Docker Q1 2027) | Hosted only | Hosted only | Varies |
| Supported clients | 7 + ChatGPT bridge | Limited | Limited | Varies |
| Pricing | Free – $40/mo (no MCP gate) | Included at $29/mo | €20–39/mo | — |
Also available as an AI Skill for automation
The same skill that runs in MCP runs in chat, reports, alerts, and the API.
Author once, deliver everywhere. 49 builtin skills ship today; custom skills land via
.gskill packaging.
Build agentic workflows using a scalable developer analytics infrastructure that check sprint health before standup, flag risky PRs before merge, generate weekly digests automatically, or trigger onboarding reviews when a new hire hits their 30-day mark.