Crustdata
CrustData is an AI-powered data intelligence platform that provides real-time company and people data via APIs and webhooks, empowering B2B sales teams, AI SDRs, and investors to act on live signals
Verdict
Common use cases
- Qualify inbound leads with headcount and funding data
- Track hiring velocity at target accounts
- Build outreach lists of decision makers
- Monitor competitor funding milestones
- Spot buying signals from job postings
Integration
- Vendor
- Crustdata
- Category
- crm
- Auth
- API_KEY
- Tools
- 14
- Composio slug
crustdata
Tools
- Enrich person screener
The screener person enrich endpoint enriches person data by providing additional information based on the given query. it allows users to retrieve detailed information about individuals, which can be useful for various purposes such as cust
- Fetch headcount by facet timeseries
Retrieves headcount data as a timeseries with faceted analysis capabilities. this endpoint allows users to fetch detailed headcount information over time, applying complex filters, pagination, and sorting. it's particularly useful for hr an
- Fetch investor portfolio data
Retrieves comprehensive investor portfolio data from the data lab section of the crustdata api. this endpoint provides access to detailed information about investor portfolios, including investment holdings, performance metrics, and other r
- Filter decision makers data
Filters and retrieves decision maker data from the crustdata b2b saas integration platform based on complex criteria. this endpoint allows for advanced querying of decision maker information using a combination of filters, pagination, sorti
- Post funding milestone timeseries data
The fundingmilestonetimeseries endpoint retrieves time-series data related to funding milestones for companies. it allows for complex querying of funding events over time, with flexible filtering, pagination, and sorting options. this endpo
- Post headcount timeseries data
Retrieves filtered and sorted headcount timeseries data from the crustdata data lab. this endpoint allows for complex querying of historical headcount information, enabling users to analyze workforce trends over time. it supports advanced f
- Post job listings table data
This endpoint retrieves filtered and sorted job listings data for specified company tickers from a chosen dataset in the crustdata platform. it allows for highly customizable queries with complex filtering conditions, pagination, and sortin
- Post web traffic data
Retrieves filtered and sorted web traffic data from the crustdata platform. this endpoint allows for complex querying of web traffic information using nested conditions and logical operators. it supports pagination for handling large datase
- Retrieve linkedin posts
Retrieves linkedin posts for a specified company using crustdata's screener functionality. this endpoint allows users to gather social media data from linkedin, which can be used for analyzing company activity, engagement, and sentiment. it
- Screener company information
The getcompanyscreener endpoint allows users to search and filter companies based on various criteria such as headcount, growth rate, funding, and more. it provides a powerful way to identify specific companies that meet predefined conditio
- Screen metrics and filter conditions
The screendata endpoint enables advanced data screening and filtering on the crustdata platform. it allows users to construct complex queries for retrieving specific datasets based on custom metrics, filtering conditions, and sorting criter
- Search companies with filters
The companysearch endpoint enables users to search and filter companies using the crustdata api. it provides a powerful mechanism for querying company data based on multiple criteria, supporting complex filtering and pagination. this endpoi
- Search for job id in screener
The screener person search endpoint allows users to search for persons associated with a specific job id within the crustdata b2b saas integration platform. this post request accepts a json payload containing a job id and returns relevant p
- Search linkedin posts by keyword
This endpoint enables searching for linkedin posts using a specific keyword. it allows users to retrieve relevant content from linkedin by specifying a search term, along with options for pagination, sorting, and filtering by post date. the
Setup
Setup guide
- 11. In Switchy, open the Space where you want to use Crustdata and click the integrations panel on the right. 2. Search for Crustdata and click Connect. 3. You'll be prompted to paste an API key — log into your Crustdata account at crustdata.com, navigate to Settings > API Keys, and generate a new key with read access to the datasets you need (person enrichment, company data, job listings). 4. Copy the key and paste it into Switchy's prompt, then click Authorize. 5. Switchy confirms the connection and shows which tools are now available. 6. Test it by typing '@Crustdata enrich this person: [LinkedIn URL]' in the Space chat — you should see profile data appear within seconds. 7. If the response is empty or errors, double-check your key's scopes and usage limits in the Crustdata dashboard.
What teammates see: by default, memories from Crustdata are scoped to the Space (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Spaces have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
Enrich Prospect Profile
@Crustdata enrich this person: [paste LinkedIn URL or email]. Return their current role, company headcount, recent funding, and any job changes in the past year.Open in a Space →
Track Hiring Velocity
@Crustdata fetch headcount timeseries for [company ticker] from six months ago to today. Highlight any departments growing faster than 20% quarter-over-quarter.Open in a Space →
Find Decision Makers
@Crustdata filter decision makers at companies in [industry] with 50-500 employees. Return VP and C-level contacts in sales or marketing, sorted by company growth rate.Open in a Space →
Monitor Competitor Funding
@Crustdata get funding milestone timeseries for [competitor ticker] over the past two years. Flag any Series B or later rounds and the lead investors.Open in a Space →
Spot Buying Signals
@Crustdata pull job listings for [target company ticker] posted in the last 30 days. Highlight any VP or director roles in sales, marketing, or IT.Open in a Space →
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@Crustdata find decision makers at Series B SaaS companies in fintech with 50-200 employees who raised funding in the last 6 months
Based on your criteria, I found 47 decision makers across 12 companies matching your filters. The results include CTOs, VPs of Engineering, and Head of Product roles at companies like Acme Financial (Series B, $18M raised 3 months ago, 87 employees), Beta Payments (Series B, $25M raised 5 months ago, 134 employees), and similar profiles. Each record includes LinkedIn profile, company funding details, current headcount, and contact enrichment data where available. This is an illustrative example—actual results depend on Crustdata's current database coverage and your account's data access tier.
This example showcases Crustdata's ability to layer multiple B2B filters (funding stage, industry, headcount, recency) to surface targeted leads. Requires API key with decision-maker access. Note that contact enrichment quality varies by profile completeness in Crustdata's dataset, and some records may lack direct email/phone data.
@Crustdata enrich this person: Sarah Chen, VP Engineering at Quantum Labs, and tell me about her company's recent hiring trends
Sarah Chen's enriched profile shows 8+ years in engineering leadership, previously at Google and Stripe. Her LinkedIn indicates she joined Quantum Labs 14 months ago. Quantum Labs' headcount timeseries reveals they've grown from 42 to 78 employees in the past year, with 18 engineering hires in Q4 2024 alone. They're currently advertising 12 open roles (6 in engineering, 4 in sales, 2 in product). This suggests aggressive expansion mode. This is an illustrative example—actual enrichment depth depends on data availability for the specific individual and company.
This example pairs person enrichment with company growth signals, useful for sales context or competitive intelligence. The MCP combines data from multiple endpoints (person screener, headcount timeseries, job listings). Be aware that historical headcount data may have gaps for private companies with limited public footprint.
@Crustdata compare web traffic trends for our top 3 competitors over the last 90 days and identify which one is growing fastest
Analyzing web traffic for Competitor A, B, and C from December 2024 to February 2025: Competitor B shows the strongest growth trajectory with 34% increase in monthly visits (1.2M to 1.6M), while Competitor A declined 8% and Competitor C remained flat. Competitor B's traffic spike correlates with their Series C announcement in January and a product launch. Their engagement metrics (avg session duration up 22%) suggest quality traffic, not just paid acquisition. This is an illustrative example—actual traffic data granularity depends on Crustdata's web analytics partnerships.
This example demonstrates how the MCP can synthesize timeseries data into competitive insights. Web traffic accuracy varies by site size and tracking methodology—smaller companies may have incomplete data. The AI's correlation analysis (funding events, product launches) adds context beyond raw numbers, but causation claims should be verified.
Use-case deep-dives
When Crustdata beats manual LinkedIn scraping for cold outreach
A 3-person sales team at a Series A SaaS company needs 200 qualified leads per week for cold email. They filter for VP-level decision makers at companies with 50-200 headcount and recent funding rounds. Crustdata's decision-maker filter and funding milestone tools pull this in minutes, not hours of LinkedIn Premium seat-hopping. The API key auth means any rep can run the query from Switchy without waiting on eng. The threshold: if your ICP is consumer-facing or non-tech verticals, Crustdata's coverage drops fast—you'll get 30% fill rates instead of 80%. For B2B tech buyers, this is the fastest path from criteria to Salesforce upload.
Monitoring competitor hiring and funding without a research team
A 6-person product team at a growth-stage fintech watches three direct competitors. They need to know when a rival raises capital, posts engineering jobs, or sees web traffic spike—signals that inform roadmap bets. Crustdata's headcount timeseries, funding milestone, and web traffic tools surface these changes weekly. The team runs a Switchy workflow every Monday that checks all three data types and drops anomalies into Slack. The trade-off: if you need same-day alerts or sub-industry niche players, Crustdata's refresh cadence (typically weekly) lags behind paid analyst services. For quarterly planning cycles and top-50 competitor sets, this is the right speed and price.
When portfolio mapping replaces spreadsheet guesswork for fundraising
A 2-person founding team is prepping their seed deck and needs to know which VCs actually write checks in their space. They query Crustdata's investor portfolio endpoint for funds that backed 5+ companies in vertical SaaS with sub-$5M rounds in the last 18 months. The output is a ranked list with investment history, not a generic Crunchbase export. This cuts intro-request prep from a week to an afternoon. The boundary: if you're targeting corporate VCs or non-US funds, coverage thins out—you'll need to supplement with manual research. For institutional investors in North American tech, this is the cleanest single-source answer.
Frequently asked
What does the Crustdata MCP do in Switchy?
It pulls B2B company intelligence — headcount trends, funding milestones, job postings, web traffic, investor portfolios, and decision-maker profiles — directly into your Switchy workspace. You query Crustdata's datasets without leaving the chat, so your team can research prospects, track hiring signals, or validate market assumptions in real time alongside other tools.
Do I need a Crustdata account to use this MCP?
Yes. You need an active Crustdata subscription and an API key. The MCP uses API_KEY authentication, so whoever connects it in Switchy must paste their key from the Crustdata dashboard. Free-tier keys work if Crustdata offers one, but rate limits and dataset access depend on your plan with them.
Can the Crustdata MCP write data back to my CRM?
No. This MCP is read-only — it fetches enrichment and intelligence data from Crustdata's datasets but doesn't push records into Salesforce, HubSpot, or any other system. If you want to sync enriched profiles to your CRM, you'll need to copy the output manually or use a separate automation tool outside Switchy.
How is this different from querying Crustdata's API directly?
The MCP wraps Crustdata's REST endpoints so you can ask natural-language questions in Switchy instead of writing JSON filters and pagination logic. You get the same data, but the AI handles query construction, result parsing, and combining Crustdata insights with other tools in your workspace — no Postman or Python scripts required.
Who on the team should connect the Crustdata MCP?
Whoever owns your Crustdata subscription and has the API key. Typically a revenue ops lead, sales engineer, or head of growth. Once connected in a shared Switchy workspace, anyone on the team can query Crustdata datasets through chat — they don't need individual keys or Crustdata logins.