Crunchbase API Alternatives
Most people land here for one of three reasons: the Crunchbase API sits behind sales-gated data licensing with no free tier, the dataset is strongest where funding events exist and thinner in the long tail, or an AI agent needs programmatic company search and Crunchbase publishes no official MCP server. This page compares the credible alternatives for company discovery, honestly and with sources.
Every claim about another product links to its current public source. If a vendor changes pricing or access, their own page is the source of truth.
Quick comparison
| Product | Coverage | Query model | API access | MCP | Pricing model | Free tier |
|---|---|---|---|---|---|---|
| Canonical | Verified company graph built for long-tail company discovery | Natural language, interpreted into editable criteria; structured filters | Self-serve REST API and Python SDK | Yes — open, self-serve MCP server (OAuth) | Usage-based credits; self-serve plans | 250 free credits on signup |
| Crunchbase | Funding-data heritage, now positioned around AI predictions | Filters and saved searches; Scout AI assistant on paid plans | Sales-gated — API sold via data licensing, no self-serve signup | No official MCP server (third-party only) | Custom, sales-negotiated licensing | No free API tier |
| Exa | Web-scale search index; entity lists via Websets | Natural-language web search; Websets criteria you can review and edit | Self-serve with published usage-based pricing | Yes — official MCP server | Per-request, usage-based; published | Free monthly request allowance |
| Parallel | Live-web research at query time; FindAll builds entity lists | Prompt/task-based research APIs; natural-language entity search | Self-serve API key signup | Yes — official Search and Task MCP servers | Per-request, usage-based; published | Free request allowance |
| Harmonic | Startup-focused database (35M company records) | Console filters and saved searches; Scout AI agent for natural language | Sales-gated; demo-led onboarding | Yes — official MCP server, for existing customers | Not published; contract via sales | No self-serve free tier |
| Grata (Datasite) | Middle-market and founder-owned private companies (21M+) | Agentic AI search plus filters and similar-company search | Demo-led; no self-serve signup | Yes — official MCP server, customer-gated | Named tiers, prices not published | No free tier; demo only |
| People Data Labs | Bulk data infrastructure: 70M+ company profiles | Structured only — Elasticsearch DSL or SQL queries | Self-serve with published volume-based pricing | No official MCP server (third-party wrappers only) | Per-record plans, volume-based; published | Free plan — 100 records per month |
Vendor claims link to their public sources; their current pages take precedence.
Canonical
Purpose-built company search: describe the companies you want in plain English, see exactly how the query was interpreted as structured criteria — and adjust it — before running, then get a verified shortlist with per-criterion match status and source-backed evidence. Searchable dimensions include industry and profile, geography, employee size, funding stage, investors, similar-companies, and exclusions. Access is self-serve across the app, REST API, Python SDK, and an open MCP server, so the same search works for an analyst and for an agent.
Limitations: Not a deep-dive data warehouse: no editorial funding-round timelines or investor relationship graphs the way Crunchbase curates them, and no prediction models. Canonical optimizes for finding the right companies — especially the long tail — not for exhaustive per-company field depth.
Best for: Investors sourcing against a thesis, analysts building market maps, business development and recruiting teams building targeted lists, and AI agents that need company search over MCP or API without a sales cycle.
Example query: “post-Series A companies in Europe building battery recycling or second-life storage, excluding consultancies”
Benchmark
They search the same web.
We find different companies.
Same query across Canonical, Exa, and Parallel. Canonical surfaced 48 companies the others missed.
50 companies found by Canonical.
The broadest shortlist from the same query.
48 only found by Canonical.
Long-tail companies missing from the other result sets.
Canonical returned the broadest shortlist from the same query.
The benchmark pooled 96 companies across all platforms. Canonical surfaced 50 of them, more than either alternative.
Almost zero overlap.
Only 3 companies appeared on more than one platform. Canonical surfaced 48 companies no other platform returned.
| Canonical | Exa | Parallel | |
|---|---|---|---|
| Canonical | 48 | 2 | 0 |
| Exa | 2 | 28 | 1 |
| Parallel | 0 | 1 | 17 |
Diagonal shows companies only found by that platform. Off-diagonal cells show pair overlap.
More results, less waiting.
Canonical returned a broader evidence-backed shortlist in under 10 seconds, while alternatives took minutes to return fewer results.
Different indexes, different companies.
A sample of what each platform surfaced for the same query.
Niche companies purpose-built for the query.
- 01 Schematic
- 02 Togai
- 03 Andra Labs
- 04 Flowglad
- 05 Kickplan
- 06 Stykite
- 07 Amberflo
- 08 RevenueCat
- 09 DevCycle
+ 41 more
Mid-tier developer tools with strong web presence.
- 01 Ably
- 02 Replit
- 03 Cursor
- 04 Weights & Biases
- 05 Contentful
- 06 n8n
- 07 Tabnine
- 08 AssemblyAI
- 09 Chargebee
+ 22 more
Large, well-known companies many developers could name from memory.
- 01 AWS
- 02 Microsoft Azure
- 03 Google Cloud Platform
- 04 Stripe
- 05 Twilio
- 06 OpenAI
- 07 Docker
- 08 Sentry
- 09 Vercel
+ 9 more
Exa
A general web search and retrieval API built for AI agents, with strong latency and a web-scale index. Company list-building lives in Websets: describe what you want in natural language, confirm or edit the generated criteria, and verification agents check each result against the live web. Self-serve, published pricing, an official MCP server, and a free monthly request allowance.
Limitations: Company search is one vertical of a horizontal product — Websets covers people, papers, and other entities too, and results are built from web evidence per run rather than queries over a maintained, verified company graph. Costs scale with per-result verification on large lists.
Best for: Teams that also need general web search, content extraction, or research workflows beyond company discovery, and agent builders already standardizing on a web-search API.
Parallel
High-accuracy web research infrastructure for agents: search, extraction, deep research, and FindAll — natural-language entity discovery that assembles verified, cited entity lists from the live web. Self-serve signup, per-request published pricing, a free allowance, and official MCP servers (the Search MCP works without an API key).
Limitations: Coverage comes from researching the live web at query time, not from a maintained company dataset — there are no standing structured company profiles to filter against, and entity-search results carry name, URL, and description rather than firmographic fields. Deep research runs trade latency for accuracy.
Best for: Agent builders who want evidence-backed web research as infrastructure and are assembling their own company-data layer on top.
Harmonic
A startup-focused database (35M company records, 195M people records) built for venture workflows: saved searches that surface net-new matches, CRM sync, REST and GraphQL APIs, a Scout AI agent for natural-language questions, and an official MCP server for existing customers.
Limitations: Access is sales-led end to end — no self-serve signup, no published pricing, no free tier — and the dataset is purpose-built for venture-relevant startups rather than the full company universe. If your targets are not startups, coverage focus works against you.
Best for: Venture and growth investors with a sales-cycle budget who want a startup-specific system of record integrated with their CRM.
Grata (a Datasite company)
Private-markets deal sourcing with a differentiated dataset: middle-market, founder-owned, and bootstrapped companies that funding-event databases miss (21M+ private companies). Agentic AI search and similar-company search on top of traditional filters, an official MCP server, and deal workflow depth from the Datasite ecosystem.
Limitations: Demo-led access only — no self-serve signup, tier names but no published prices, no free tier — and the MCP server is provisioned through your Grata rep rather than open signup. Strongest historically in the US middle market; if you need API-first programmatic access today, the path runs through sales.
Best for: Private equity firms, investment banks, and corporate development teams sourcing middle-market acquisition targets.
People Data Labs
Data infrastructure rather than a search product: bulk person and company datasets (70M+ company profiles), enrichment and search APIs, self-serve plans with published volume-based pricing, and a genuinely free tier (100 records per month). If you are building your own company-data product, this is the raw-material option.
Limitations: Queries are Elasticsearch DSL or SQL — there is no natural-language interface and no end-user search UI, so someone on your team is writing queries and building the experience. No official MCP server; record quality varies across the long tail, as with any aggregated bulk dataset.
Best for: Engineering teams building data products or internal tools who want raw company and person data under their own roof.
Frequently asked questions
Is there a free Crunchbase API alternative?
Yes. Canonical includes 250 free credits on signup with self-serve API, SDK, and MCP access. Exa and Parallel offer free monthly request allowances on self-serve accounts, and People Data Labs has a free plan of 100 records per month. The Crunchbase API itself has no free tier — access is sold through sales-negotiated data licensing.
Which company data APIs support MCP?
Canonical, Exa, and Parallel run official MCP servers you can connect to self-serve. Harmonic and Grata also ship official MCP servers, but both are provisioned for existing customers rather than open signup. Crunchbase and People Data Labs publish no official MCP server — only third-party wrappers exist.
Can I search for companies with natural language instead of filters?
Increasingly yes, in different shapes. Canonical is natural-language-first and shows you the interpreted criteria to edit before running. Exa's Websets and Parallel's FindAll take natural-language descriptions and verify candidates against the live web. Crunchbase and Harmonic added AI assistants (both named Scout) on top of their filter systems, and Grata markets agentic search. People Data Labs remains structured-query only — Elasticsearch DSL or SQL.
Do these alternatives cover private, long-tail companies?
Coverage models differ more than marketing suggests. Funding-centric databases are strongest where funding events exist. Web-research products reach anything with a web presence but rebuild evidence per query. Grata specializes in founder-owned middle-market companies. Canonical maintains a verified company graph built specifically for long-tail discovery — the benchmark on this page measures that difference.
When should I just use the Crunchbase API?
When you need editorially curated funding histories, prediction models, or licensed redistribution of company data inside your own product — and you have the budget for an annual data-licensing contract. For describe-and-shortlist company discovery, the self-serve alternatives above are faster to start with.