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Engineering context for AI agents
An MCP server for your engineering workflow. PRs, reviews, bottlenecks, and workload — instantly inside Claude, Cursor, and Copilot. Free forever.
Pre-indexed engineering history
Efiros imports and indexes your Git history — so agents query years of workflow data instantly, without API limits or slow searches
Answers inside your AI agent
Ask what's blocked, who's overloaded, or what to review first — and get real answers directly inside your AI workflow
Built for real engineering teams
Self-hosted MCP server with read-only metadata access. No employee monitoring. Your data stays private
Not another dashboard
Efiros gives AI agents live engineering context for reviews, queues, bottlenecks, and delivery decisions
See the difference
Before Efiros
You're shipping more code. You're not shipping faster.
A PR has been open for 5 days. Nobody noticed until the release slipped
One engineer reviews most of the code. They're close to burnout. Your agent keeps assigning them more
AI tripled your PR volume. Your merge time got worse
Native MCP servers weren't built for analytics — rate limits, timeouts, and no history make real engineering queries impossible
With Efiros
Your agent sees what your team sees
"What should I review first?" — shows the PR blocking delivery right now
"Is anyone blocked?" — finds work with no reviewers assigned
"Can we ship this week?" — checks open PRs, review progress, and blockers instantly
All from your git history. No surveys. No standups. Just answers inside your AI tools
Questions your agent can answer
"What should I review first?"
Efiros ranks your review queue by wait time, blocker impact, ownership, and PR size. Your agent gives you the top 3 in one sentence
"Why is this PR stuck?"
Efiros traces the wait chain — who's blocking, since when, and why. Your agent answers with context from your full engineering history
"Who's overloaded this week?"
Spot review concentration and ownership bottlenecks before they slow the team down. No scoring. Just system-level signals
"Are we shipping faster?"
Cycle time from first commit to production — per team, repo, and week. Real delivery numbers from your git history
What our users say
"We had dashboards and reports, but conversations about work were still based on opinion rather than shared understanding. Efiros helped us see where interaction patterns and coordination friction were actually occurring — not just that metrics changed, but why work felt stuck. That gave us a common language to address issues without finger-pointing and improve how teams collaborate over time."
"We used plenty of metrics, but none explained what was happening between teams and roles. Efiros revealed interaction patterns that explained where work piled up — in reviews, handoffs, or coordination — and helped us turn that into actionable insights. The shared clarity it created across engineering and leadership was a game changer for our planning conversations."
"What stood out was how Efiros transformed raw activity into meaningful signals about how teams actually interact. We could confidently share these interaction pattern insights with product, leadership, and risk stakeholders — without any suggestion of judging individual performance. This made cross-functional alignment feel grounded and constructive."
faQ
How long does setup take?
Usually under 5 minutes. Run one command, connect your GitHub or GitLab repository, and your AI agent can start querying engineering workflow data immediately.
What can AI agents actually ask Efiros?
Questions like: "What should I review first?" "Why is this PR stuck?" "Who's overloaded this week?" "Are we shipping faster than last month?" Efiros gives agents real answers using your Git history and workflow data.
Why not just use the native GitHub MCP?
GitHub MCP works well for basic repository actions, but engineering analytics quickly hit API limits and timeout constraints. Efiros continuously imports and indexes your Git history so agents can query years of delivery data instantly.
What data does Efiros analyze?
Efiros analyzes Git workflow metadata including pull requests, reviews, commits, review events, merge activity, cycle time, and workload distribution.
Does Efiros access our source code?
No source code analysis by default. Efiros focuses on Git workflow metadata such as PRs, reviews, commits, and delivery events.
Can Efiros work inside our infrastructure?
Yes. The MCP server is self-hosted and runs inside your environment with read-only repository access.
Does Efiros track individual developer productivity?
No. Efiros focuses on system-level workflow signals such as bottlenecks, queues, review load, and delivery flow — not employee monitoring or productivity scoring.
Is Efiros free?
Yes. The self-hosted MCP server is free. Dashboard features are free for teams up to 10 developers.