greenhouse · MCP Server

Greenhouse + Improvado MCP — Recruiting Pipeline, Instantly Queryable

Improvado MCP extracts candidate, pipeline, and hiring performance data from Greenhouse and makes it queryable by AI agents in plain English.

46K+ metrics ·Read & Write access ·500+ platforms ·<60s setup

Read

Instant Recruiting Intelligence From Greenhouse

Stop exporting Greenhouse reports for every stakeholder request. Improvado MCP connects your AI agent to Greenhouse so talent teams and hiring managers can query pipeline data conversationally.

Example prompts

"How many candidates are active per open role?"

30 min → 1 min

"What's our stage conversion rate from screen to offer?"

1 hr → 2 min

"Show average time-in-stage by job department"

45 min → 1 min

Works with Claude ChatGPT Cursor +5

Write

Push Recruiting Insights Into Planning Systems

After querying Greenhouse, push pipeline summaries, bottleneck flags, and headcount updates to planning tools and stakeholder docs without switching platforms.

Example prompts

"Export new hires from last 30 days to HRIS queue"

Manual → auto

"Log stalled requisitions to headcount tracker"

1 hr → 3 min

"Write weekly pipeline report to shared doc"

2 hrs → 5 min

Every action logged · Fully reversible · SOC 2 certified

Monitor

Monitor Pipeline Health Across All Requisitions

Set AI watches on requisition age, stage velocity, and scorecard completion rates. Improvado MCP surfaces hiring risks early so nothing slips through.

Example prompts

"Alert when any role exceeds 45-day time-to-fill"

Manual → auto

"Track scorecard submission rate per interviewer weekly"

2 hrs → 5 min

"Monitor offer decline rate by department monthly"

1 hr → 2 min

Alerts sent to Slack, email, or your AI agent

Full cycle

The Closed Loop: Read → Decide → Write → Monitor

Your AI agent doesn't just surface data — it acts. Adjust pricing, update product descriptions, manage inventory, apply discounts — all through natural language. The MCP server translates intent into API operations.

Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.

Ideate

Launch

Measure

Analyze

Report

Iterate

One conversation. All six phases. Every platform.

The daily grind

Common problems. Direct answers.

Challenge 1

Incomplete Scorecards Delay Hiring Decisions

The problem

Interviewers who don't submit scorecards on time create decision-making bottlenecks, extending time-to-offer and frustrating candidates who are fielding competing offers.

How MCP solves it

Improvado MCP surfaces scorecard completion rates by interviewer and role, letting talent teams follow up proactively before delays escalate.

Try asking

Which interviewers have outstanding scorecards from this week?

Answer in seconds

All data sources, one query

Challenge 2

Sourcing Quality Unclear Without Deep Analysis

The problem

Understanding which sources produce candidates who pass the technical screen and reach offers requires manual data joining that most teams don't have bandwidth for.

How MCP solves it

Ask one question and get source-to-offer funnel analysis across all channels. Improvado MCP joins Greenhouse sourcing and stage data automatically.

Try asking

Which sources generate candidates reaching final rounds?

Full detail preserved

No data loss on export

Challenge 3

Headcount Reporting Consumes Recruiter Time

The problem

Weekly recruiting reports require pulling Greenhouse exports, cleaning stage data, and formatting summaries — easily consuming two to three hours of recruiter time.

How MCP solves it

Generate ready-to-share recruiting summaries in seconds. Improvado MCP queries Greenhouse and returns structured results formatted for stakeholder consumption.

Try asking

Summarize this week's pipeline status by business unit

Unified data model

Compare anything side by side

👥 Teams

One Framework. Five Roles. Zero Setup.

Same MCP connection, different workflows for every team member. Each role asks in natural language — the MCP server handles the complexity (rate limits, auth, schema normalization, governance) behind the scenes.

Agency CEO

Portfolio health. Client risk. Revenue signals.

Media Strategist

70% strategy, not 70% ops. Auto campaign QA.

Marketing Analyst

Zero wrangling. Cross-platform. AI narratives.

Account Manager

QBR decks auto-generated. Call prep in 30s.

Creative Director

Performance-to-brief. Predict winners before spend.

FAQ

Common questions

What Greenhouse data does Improvado MCP expose?

Improvado MCP surfaces job postings, candidates, applications, pipeline stages, scorecards, interview kits, offers, hires, and sourcing attribution data from Greenhouse.

Can this integration access custom fields in Greenhouse?

Yes. Custom candidate and application fields configured in Greenhouse are accessible via Improvado MCP, making it possible to query organization-specific data points.

Does this work with Greenhouse Recruiting and Onboarding?

Improvado MCP primarily covers Greenhouse Recruiting data. Onboarding data availability depends on API exposure in your Greenhouse account configuration.

How does this handle candidate data privacy?

All data access runs through your configured Greenhouse API credentials. Improvado MCP respects all Greenhouse permission levels and does not expose data outside your access scope.

Can hiring managers query their own pipeline without recruiter help?

Yes. With appropriate Improvado permissions, hiring managers can ask their AI agent for live updates on their open roles without involving the recruiting team.

Can I combine Greenhouse data with HRIS or payroll data?

Yes. Improvado connects multiple HR tools, allowing you to combine Greenhouse recruiting data with HRIS onboarding records or workforce planning data in a single query.

Stop Reporting. Start Executing.

Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.

SOC 2 Type II GDPR 500+ Platforms