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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.

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Efiros setup
① connect repository ② connect Claude ③ ask questions
Claude + Efiros MCP
Claude + Efiros MCP
① connect repository ② connect Claude ③ ask questions

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

Engineering audit

Find out what slow delivery is actually costing you

Most teams lose 40–60% of delivery capacity to reviews, approvals, and coordination. We analyze your repository data — no interviews, no sprint disruption — and tell you exactly where work gets stuck and what fixing it is worth.

See the audit

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

GitHub Connection Not connected Connect Sync Interval: Real-time Client ID: Gp4d23c444zx6y6q from GitHub
0

"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

0Excellent (90+) 0Good (70-89) 0Fair (50-69) 0Poor (<50) Frederick Manning Vibe Score 89 Velocity 15 Quality 9 Reliability 9
DevelopmentTrends Week 1 Week 3 Week 5 Week 3 20 Commits 8 Pull requests 7 Reviews Review Speed 4.2h Last analyzed: 04/05/2026

"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

Emily Carter

Engineering Manager, Scale-up

"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."

Ryan Patel

CTO, B2B SaaS company

"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."

Daniel Moore

Head of Engineering, FinTech

"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.

Your repo, inside your AI agent

Free self-hosted MCP server for your engineering workflow. No credit card. No sales call.

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