# The structured data layer your AI agents run on.

Agents reason poorly over flat exports — they get text to search, not structure to traverse. GraphIQ.ai exposes the identity graph through a native MCP server, so autonomous agents query relationships directly and act with grounded context.

## Give an agent a list and it guesses. Give it a graph and it reasons.

### The old way

CSVs and plain REST endpoints — agents pattern-match strings and infer connections that aren't really there.

### With GraphIQ.ai

A native MCP server — agents traverse resolved entities and relationships, each carrying provenance and a confidence score.

## How it works

### From prompt to grounded action.

01

### Connect the MCP server

Point your agent or LLM at the GraphIQ.ai MCP endpoint.

02

### Query the graph

Agents resolve entities and traverse relationships in-context, as tools.

03

### Ground every answer

Responses carry provenance and confidence — verified edges, not guesses.

04

### Act in the loop

Agents write resolved results back to CRM, Clay, or downstream tools.

## What it unlocks

- Fewer hallucinated relationships
- Grounded, cited answers
- Real-time graph traversal
- One data layer for every agent

## FAQ

### Frequently asked questions

**What is the MCP server?**  
A Model Context Protocol endpoint that lets LLMs and agents call GraphIQ.ai directly — resolving entities and traversing the graph as native tools, with no export step in between.

**Do I need Clay or a CRM to use it?**  
No. Agents can query the MCP server directly; Clay and your CRM are optional activation targets for whatever the agent resolves.

**How do you prevent hallucinated connections?**  
The graph returns resolved entities with confidence scores and provenance, so agents act on verified relationships instead of inferring them from raw text.

## Ground your agents in the graph.

Connect the MCP server and let your agents reason over real relationships.