Dreamdata

Map the journey, prove the revenue

MCPAPINative readiness

About

What is Dreamdata

Dreamdata collects event data across a B2B tech stack, stitches known, anonymous, and cookieless touchpoints into a unified account-level journey, and connects that data to revenue outcomes through customizable attribution models. It is built for marketing, RevOps, and GTM leads at mid-market and enterprise companies who need to tie spend to pipeline without relying on last-touch guesswork. The most distinctive capability is its IP-to-company resolution engine, which claims to identify up to 80% of visiting companies — feeding firmographic context directly into audience activation and sales alerts. Teams can push those audiences to major ad platforms, trigger sales notifications on high-engagement accounts, and generate AI-summarized ROI and ROAS reports without leaving the platform. The limitation to know: Dreamdata is purpose-built for B2B account-based motions — teams running high-volume B2C or transactional models will find the data model and reporting structure a poor fit.

Data & Discovery

Capabilities

Key features

Intent signals

surfaces buying triggers (funding, hiring, churn

AI capabilities

autonomous multi-step actions

Data

intent signals, visitor identification, firmographic + tech-stack data

Also ships

official SDK

Outbound webhooks

event-driven integrations

Our verdict

Vanderbuild take

For Marketing and RevOps teams that need to connect visitor identification, intent signals, and account research to actual revenue, Dreamdata is one of the few platforms that attempts to do all three in a single data model rather than stitching three separate tools together. On the agentic readiness front, this is as ready as it gets — native MCP server support means AI agents can query journey data, pull firmographic context, and trigger activation workflows without a human in the loop, making it a credible orchestration layer for agentic GTM stacks. That said, enterprise-priced custom tiers mean procurement will be involved, and the free plan is more of a proof-of-concept entry point than a production tier for growing teams. The honest limitation: if your attribution needs are straightforward or your sales cycle is short, the depth of Dreamdata's data model becomes overhead rather than advantage — simpler UTM-based tools will get you 80% of the way at a fraction of the cost.

Mateusz Sekta

Founder, vanderbuild

The wedge

Agentic stack profile

MCP server

Yes

Live MCP server — agents can call this tool directly.

Dreamdata documents that customers can enable an MCP server for their Data Warehouse by using Google BigQuery’s managed remote MCP server (endpoint https://bigquery.googleapis.com/mcp). The setup involves enabling the BigQuery MCP API, creating an OAuth client, and ensuring appropriate IAM roles, allowing AI agents (e.g., Claude) to query Dreamdata warehouse tables via MCP.

Open MCP →

API

SDK only

Programmatic access available.

Access via official SDK only. No raw HTTP endpoint exposed.

API docs →

Agentic readiness

Native

Built for agents from the ground up.

MCP server + agent-friendly API + at least one autonomous workflow out of the box. The bar for 'Native' is high — only a handful of tools currently qualify.

Stack role

Signal source · Researcher

Where this tool slots into an agentic pipeline.

Plays the role of Signal source + Researcher in an agentic pipeline. Use it to surface buying intent — funding, hiring, job changes, web visits; generate per-account briefings and qualification dossiers.

Compare

Dreamdata alternatives

Tools that solve a similar problem — compared at a glance.

Dreamdata(this tool)

Pricing: Freemium
Budget: $$$$
Best for: Marketing, RevOps

Readiness: Native
MCP: Yes
API: SDK only

Common Room

Pricing: Workspace-based
Budget: $$$$
Best for: RevOps, GTM Lead

Readiness: Native
MCP: Yes
API: REST

Hyros

Pricing: Usage-based
Budget: $$
Best for: Marketing, GTM Lead

Readiness: Native
MCP: Yes
API: REST

Answers

Frequently asked questions

Does Dreamdata have an MCP server?

Yes — Dreamdata exposes a Model Context Protocol server. Dreamdata documents that customers can enable an MCP server for their Data Warehouse by using Google BigQuery’s managed remote MCP server (endpoint https://bigquery.googleapis.com/mcp). The setup involves enabling the BigQuery MCP API, creating an OAuth client, and ensuring appropriate IAM roles, allowing AI agents (e.g., Claude) to query Dreamdata warehouse tables via MCP. See the MCP docs at https://dreamdata.io/blog/using-ai-agents-with-dreamdata-via-mcp.

Does Dreamdata have a public API?

Yes — Dreamdata ships a SDK only API. Docs: https://developer.dreamdata.io/client-side/api/.

How much does Dreamdata cost?

Dreamdata: pricing is freemium, expect enterprise tier ($$$$) spend. Full pricing page: https://dreamdata.io/pricing.

Who is Dreamdata best for?

Dreamdata is built for Marketing, RevOps, GTM Lead. Fits Mid-market (50-500), Enterprise-sized teams.

How well does Dreamdata fit an agentic sales stack?

Tier: Native. Has both an MCP server and an agent-friendly API — drops into an agentic stack with minimal glue code.

Quick spec

MCP serverYes ↗

APISDK only ↗

ReadinessNative

Stack roleSignal source, Researcher

Pricing

Freemium

$$$$

Vendor pricing →

Ideal customer

Growth stage

Scale-up · Enterprise

Company size

Mid-market (50-500) · Enterprise

Best for

Marketing · RevOps · GTM Lead