MCP server — GraphIQ.ai
The identity graph as an MCP server. Your AI agents query it natively.
Give your AI assistants direct access to our full 287M organization identity graph — no wrapper code, no token plumbing. Connect over streamable HTTP, and tools and clean, model-ready data are available the moment you connect.
streamable HTTP · https://app.graphiq.ai/mcp
Connect via streamable HTTP at https://app.graphiq.ai/mcp. Tools are discovered on the initial handshake. Payloads are pre-shaped for model context windows. No wrapper code, no token serialization overhead, no per-seat caps. Below: the four protocol-layer capabilities that make the integration work, and the four graph tools your agents discover on connection.
- search_organizations
- search_employment_route
- search_news
- list_industries
Shift your AI toolchains from rigid text lookups to dynamic graph reasoning.
Standard REST endpoints require an engineer to pre-program exactly when an application should fetch a record, forcing automated systems into rigid, step-by-step tracks. If your workflow encounters a multi-subsidiary enterprise or an unexpected corporate relocation pattern, traditional applications fail because they lack baseline relationship context. Model Context Protocol fundamentally shifts how AI software runs. By providing a semantic knowledge graph straight to your agent's reasoning loop, the model behaves like an experienced analyst. The agent independently determines when to call a tool, traverses complex corporate family trees to verify subsidiary boundaries, and evaluates real-time market entry signals to craft personalized outbound approaches — grounded completely in verifiable truth.
Four capabilities. One native MCP protocol layer.
Dynamic Tool Discovery.
Upon initial handshake, your connected LLM coworkers instantly discover and understand our underlying data capabilities, including all four available tools: search_organizations, search_employment_route, search_news, and list_industries.
Dual Authentication Mechanics.
Connect autonomous backend agents and CLI toolchains securely via standard API Keys (X-API-Key). For interactive, human-in-the-loop work environments, authorize enterprise access loops using standard OAuth 2.0 user browser sign-ins.
Token-Optimized JSON-LD Payloads.
The server responds with semantic, pre-resolved entity context designed specifically to fit into model context windows, stripping out structural data noise to save on token overhead.
Access Governance.
Scope what each agent can reach. Keys carry read access across the graph, and you can provision, rotate, or revoke them per workspace as you add agents.
Where does MCP agent access connect your GTM.
| Approach | What it is | Where it breaks |
|---|---|---|
| CSV Export + RAG | Data export from ZoomInfo/Apollo into a vector store; agent queries embeddings | Data goes stale immediately. No graph hierarchy. Agent retrieves flat text passages, not resolved entities. |
| REST API Wrapper | Custom code wrapper around a legacy database REST API, exposed as an agent tool | Significant engineering overhead. Vendor schemas weren't designed for agent runtime reasoning. |
| CRM-as-Context | Agent queries Salesforce or HubSpot directly via native CRM APIs | CRM contains only data your team manually maintains. Fragmented records, no external signal tracking. |
| GraphIQ.ai MCP | Native Model Context Protocol integration into the full identity graph | Real-time. Graph-structured. Relationship-native. Zero wrapper code. |
Frequently asked questions
Is our data connection restricted to specific LLM model providers or clients?
No. Because MCP is a completely provider-agnostic standard, our server functions out-of-the-box across any protocol-capable environment. This includes Anthropic Claude (claude.ai connectors, Claude Desktop, Claude Code), OpenAI (Responses API, Agents SDK), LangChain networks, LangGraph architectures, or custom internal Python setups.
How does the MCP server ensure tenant isolation and workspace security?
Every session initiated via an API key or an authorized OAuth token runs within an isolated environment. Automated agents can only visualize, reason over, and interact with data boundaries mapped directly to your enterprise plan credentials, preventing any cross-tenant data bleed.
What is the typical latency on an MCP server call?
Standard reads return in under 200ms (production p50). The server implements Server-Sent Events (SSE) streaming on large payloads so the model can begin reasoning loops before the full data packet completes.