All 50 BigIdeasDB MCP Tools: Complete Reference for Every Data Source

Reddit tools (4 tools)

Reddit tools query live Reddit data through a hosted proxy. They are the only tools that hit an external service in real time - all other tools query BigIdeasDB's own databases. For more on Reddit research workflows, see our guide on using Reddit for market research or read how to find business ideas on Reddit.

• search_reddit - Search posts across all subreddits by keyword. Parameters: query, sort, time_filter, limit.
• fetch_subreddit - Pull posts from a specific subreddit. Parameters: subreddit, sort, time_filter, limit.
• fetch_post_comments - Get a post and its top-level comments by URL. Parameters: post_url, comment_limit.
• fetch_reddit_json - Fetch any Reddit JSON endpoint directly. Parameters: reddit_path.

Pain Points tool (1 tool)

Searches validated customer pain points across Reddit and Capterra. Each result includes severity scores, frequency, business impact, and user quotes. Learn more about pain-point-driven product research in our guide on how to find problems worth solving or read finding SaaS ideas from real user pain points.

• search_pain_points - Search by keyword, filter by source (reddit, capterra, or all). Parameters: query, source, limit.

SaaS Opportunities tool (1 tool)

Searches scored market gaps identified from Reddit discussions and Capterra reviews. Returns opportunity scores, market size estimates, MVP feature suggestions, and competitive analysis. See the best SaaS ideas backed by pain points for examples of opportunities surfaced from this data.

• search_saas_opportunities - Search by keyword, filter by source. Parameters: query, source, limit.

Capterra tools (4 tools)

Deep access to Capterra software reviews, company analysis, feature gaps, and competitive intelligence. Capterra is the richest data source in BigIdeasDB, with reviews spanning thousands of software products. See our dedicated Capterra MCP tools guide for detailed examples, or read how to mine Capterra reviews for SaaS ideas.

• search_capterra_reviews - Search reviews by keyword with rating filters. Returns pros, cons, ratings across 5 dimensions, reviewer industry, NPS scores, and alternatives considered. Parameters: query, min_rating, max_rating, limit.
• get_capterra_company_analysis - Get a full company report: sentiment scores, NPS, key strengths, critical weaknesses, competitive position, and executive summary. Parameters: company_name.
• search_capterra_feature_gaps - Find missing features users want. Returns demand intensity, request counts, use cases, and implementation complexity. Parameters: query, limit.
• search_capterra_competitive_insights - See which products users switch from and to, with advantages, disadvantages, and price comparisons. Parameters: query, limit.

G2 Insights tools (2 tools)

B2B software review insights from G2. Processed insights include pain points, proposed solutions, sentiment analysis, and detailed market analysis at the company and category level. See our G2 MCP tools guide for examples, or read finding SaaS ideas from negative G2 and App Store reviews.

• search_g2_insights - Search by company, category, or keyword. Filter by sentiment. Returns pain points, proposed solutions, and detailed insight breakdowns. Parameters: query, sentiment, limit.
• get_g2_category_insights - Get aggregated category-level analysis: top themes, pain point summaries, recommended actions, and company counts. Parameters: category, limit.

App Reviews tools (2 tools)

AI-analyzed app store data from Google Play and Apple App Store. Each app has been processed to extract pain points, feature gaps, UX issues, monetization feedback, and quick wins from real user reviews. See our App Review MCP tools guide or read how to analyze app store reviews.

• search_app_reviews - Search apps by name, genre, or developer. Returns ratings, AI-extracted pain points, missing features, UX issues, and quick wins. Parameters: query, limit.
• get_app_analysis - Get a detailed AI teardown of a specific app: pain points, missing features, UX issues, technical problems, monetization feedback, competitor advantages, and improvement recommendations. Parameters: app_name.

Upwork Signals tools (3 tools)

Demand signals extracted from Upwork job postings. These tools show what problems people are actually paying freelancers to solve - a strong signal for SaaS product opportunities. See our Upwork MCP tools guide for examples.

• search_upwork_pain_points - Search pain points from job postings by keyword. Ranked by frequency. Parameters: query, limit.
• search_upwork_opportunities - Search SaaS opportunities identified from freelance job patterns. Returns target audiences and potential features. Parameters: query, limit.
• get_upwork_category_analysis - Get category-level analysis with aggregated pain points, SaaS opportunities, and job analysis summaries. Parameters: query, limit.

Revenue Intelligence tools (4 tools)

TrustMRR verified revenue data for SaaS startups. These tools provide MRR, growth rates, profit margins, acquisition data, market clusters, and AI-generated category analysis. See our Revenue Intelligence MCP tools guide or read about the revenue intelligence platform.

• search_startups - Search startups with verified revenue. Filter by on_sale status and MRR range. Returns MRR, growth, profit margins, customers, and AI summaries. Parameters: query, on_sale, min_mrr, max_mrr, limit.
• search_deals - Search SaaS businesses for sale. Returns asking price, multiples, risk signals, and opportunity signals. Parameters: query, min_mrr, max_price, limit.
• search_clusters - Search market clusters by theme. Returns avg MRR, growth, defining traits, tech stack trends, and market gaps. Parameters: query, limit.
• get_trustmrr_category_analysis - Get category-level benchmarks: startup counts, revenue stats, top performers, rising stars, best deals, and AI market analysis. Parameters: category, limit.

Funded DB tools (3 tools)

VC- and accelerator-backed portfolio companies, each with an AI investment thesis, attractiveness score, and momentum score. Use these to see what the smartest money funds by sector and find validated markets to build into. See our Funded DB MCP tools guide or read what VCs are funding in 2026.

• search_funded_companies - Search funded companies by keyword. Filter by sector, status, country, or founding year. Returns the AI investment thesis, attractiveness, and momentum. Parameters: query, sector, status, country, min_founded_year, max_founded_year, limit.
• get_funded_company - Get full detail for one company by slug: AI investment thesis, risks, opportunity/risk signals, founders, and backing investors. Parameters: slug.
• semantic_search_funded - Concept (vector) search across funded companies. Describe a thesis or market in natural language and get semantically closest matches with similarity scores. Parameters: query, limit.

Stripe Index tools (3 tools)

Companies verified live on Stripe - the supply side of a market. Use these to confirm a niche is already monetized, gauge how crowded it is, and find the gap before you build. See our Stripe Index MCP tools guide or read the 2026 SaaS market saturation study.

• search_stripe_companies - Search companies live on Stripe by keyword and AI filters (category, business model, target customer, price tier, micro-SaaS). Returns the AI market read. Parameters: query, category, business_model, target_customer, price_tier, is_micro_saas, limit.
• get_stripe_category_sizing - Category sizing and saturation: company counts per niche, crowdedness score, micro-SaaS and agentic counts, top companies, and AI market summary. Omit category to list all by size. Parameters: category, limit.
• get_stripe_company - Get full detail for one company by slug: AI market read plus scraped site signals (pricing, free trial/freemium, API/docs, positioning). Parameters: slug.

Agent Index tools (12 tools)

Which businesses an AI agent can actually run, and what is blocking the rest. Built from a census of 7,000+ connectors across the ChatGPT apps and Claude MCP directories, broken down to 68,000+ declared tools and scored per business vertical. Use these to answer whether an agentic product is buildable for a given business type before you build it.

• get_vertical_readiness - Autopilot Readiness per business vertical: can an agent run this business end to end, or only watch it. Returns the verdict (ready / one piece short / wide open), the four score components, the blocking stack slot, and three demand fields (paying_businesses, funded_companies, complaint_volume). Lead with the verdict; the numeric score clusters into bands. Parameters: vertical, verdict, limit.
• search_agent_ideas - Product ideas scoped to a vertical and the stack slot an agent cannot reach. Defaults to ideas that survived an independent adversarial pass whose only job was to reject. Set include_evidence to attach the stored citations behind each idea. Parameters: query, vertical, idea_class, min_novelty, survivors_only, include_evidence, limit.
• search_connectors - Search connectors across both directories by platform, category, auth posture, verified tier, data domain, capability cluster and action class. Use to check whether a product or niche already has an agent surface. Every result carries a view_url into the Agent Index. Parameters: query, platform, category, authless, verified_tier, can_act, data_domain, cluster, action_class, limit.
• get_connector - One connector in full: vendor, auth posture, MCP endpoint, permissions, sensitive data types, its tools grouped by verb class, an AI-enriched profile (what it does, data domain, action class, target segment, buildability), its capability cluster, and a cross-corpus vendor_signal showing which other BigIdeasDB datasets (Funded DB, Stripe Index, TrustMRR) mention the same vendor. can_act is null when the connector publishes no capability list, which is not the same as being unable to act. Includes a view_url into the Agent Index. Parameters: connector_key.
• get_agent_coverage - Per-category coverage: how many connectors serve a category, what share can do more than read, what share the vendor built rather than the community, and how many need no auth. Weakest coverage first. Parameters: category, limit.
• get_vertical_stack - The stack behind a readiness score: every slot an operator in that vertical runs on, in order, with how many vendors fill it, how many of those have an agent surface, and which slot is blocking. get_vertical_readiness returns slots_covered as a count; this returns the rows underneath it. Also carries the same three demand fields (paying_businesses, funded_companies, complaint_volume). Vendor counts are global to the slot, not specific to the vertical, and the response says so. Parameters: vertical.
• search_software_vendors - The G2 and Capterra vendors mapped to each stack slot, filtered by whether they have an agent surface. Set has_agent_surface to false for the vendors nothing connects to, which is the build list. A null connector means no connector matched by name, not proof that none exists. Parameters: query, slot, category, source, has_agent_surface, limit.
• get_connector_growth - Monthly count of new AI connectors listed on the Claude directory, overall or for one category. ChatGPT publishes no listing date, so there is no ChatGPT series. The latest month is partial when it is the current month (see partial_latest_month). A month flagged suspect_gap is a likely source gap, not a real drop. Every result has a view_url. Parameters: platform, category.
• get_platform_coverage - Which vendors ship an AI connector to Claude, to ChatGPT, or to both, matched on vendor domain. Returns the split plus a list of vendors. Use presence=claude_only or chatgpt_only to find vendors missing from one directory, a distribution gap. Parameters: presence, category, limit.
• search_connector_gap - Companies from our Funded DB, Stripe Index or TrustMRR datasets that have shipped NO AI connector to ChatGPT or Claude. This is a build or partnership list. Matched on exact domain, so absence is a ceiling. Each row links to the company's own page. Parameters: corpus, query, category, limit.
• get_action_gap_matrix - Every connector tool classified by verb (read, write, transactional, admin, meta, unknown (unclassified)) per data domain. is_action_gap marks domains full of read tools and nearly empty of write tools, where agents can see but not act. Tool counts are mostly Claude, because few ChatGPT apps publish tool lists. Parameters: data_domain.
• search_agent_clusters - AI connectors grouped into a fixed set of capability clusters (CRM, payments, calendars...), with member count, nearby complaint demand and a whitespace score (demand per connector). High whitespace = many people describe the problem, few connectors address it. Parameters: query, limit.

SellSide DB tools (3 tools)

SaaS acquisition listings repurposed as market validation for builders - if a SaaS is being sold, the market exists. Each listing carries financials, an AI buyer thesis, opportunity signals, and red flags. See our SellSide DB MCP tools guide or read how to use acquisition listings as market validation.

• search_sellside_listings - Search acquisition listings by keyword, category, multiple, revenue, or on-sale status. Pass on_sale:true for deal flow (cheapest multiple first). Returns the AI buyer thesis and red flags. Parameters: query, category, max_profit_multiple, min_ttm_revenue, on_sale, limit.
• get_sellside_listing - Get full detail for one listing by slug: financials, tech stack, competitors, growth opportunities, key assets, reason for selling, and the full AI buyer thesis and red flags. Parameters: slug.
• semantic_search_sellside - Concept (vector) search across listings. Describe the business you want in natural language (e.g. 'founder-burnout sale, clean codebase, recurring B2B revenue') and get the closest matches by meaning. Parameters: query, limit.

Main Street Index tools (8 tools)

75,000+ small businesses for sale across 130+ industries and 100+ countries, from laundromats to HVAC firms. Use these to buy a business with real numbers (median asking multiples by industry, with n), to see why sellers say they are selling, or to find an industry underserved by software. Every figure comes with its n and disclosure rate. See our Main Street Index MCP tools guide.

• search_mainstreet_listings - Search businesses for sale by headline keyword, industry, sector, country, state, currency, asking price, earnings and stated reason for selling. Buyer filters: seller financing, real estate and real estate included, management model, training offered, owner involvement, SBA status and visa mention (AI-read; every AI field passed its 85% accuracy gate), franchise resale, home based, relocatable, price reduced, minimum earnings yield and the deal-vs-industry band. Sort by newest, price, earnings, multiple, yield or multiple vs industry and page with next_cursor. Each business is counted once. Parameters: query, industry, sector, country, state, currency, min_price, max_price, min_earnings, max_earnings, motivation, seller_financing, real_estate, real_estate_included, management_model, owner_involvement, sba_status, franchise_resale, home_based, relocatable, price_reduced, min_earnings_yield, vs_industry_band, sort, cursor, include_duplicates, limit.
• semantic_search_mainstreet - Concept (vector) search. Describe the business you want to buy in plain language and get the closest listings by meaning. Parameters: query, country, industry, sector, currency, min_price, max_price, limit.
• get_mainstreet_industry - One industry in full: definition, businesses for sale, valuation benchmarks split by currency and earnings basis (SDE vs net profit, never pooled), the Software Gap Score verdict, the Buyer Fit block for buyers (score, inputs, seller-financing and real-estate shares), and sellers' stated reasons. Also returns size-band or region breakdowns, every gap score input, and the software supply mapped to the industry with its coverage. Percentiles are withheld below n=30. Parameters: industry, region, breakdown.
• search_mainstreet_theses - Software build theses for traditional industries that survived an independent adversarial judge, strongest first. Parameters: industry, query, limit.
• get_mainstreet_brokers - Brokerage firms ranked by how many businesses they list, overall or by source, industry or country. Firm level only, never people or contact details. Parameters: source, industry, country, limit.
• get_mainstreet_listing - One business for sale in full by slug: every financial with its disclosed flag and band, premises, lease, support and training, the brokerage firm, the classified industry with the AI's confidence, software exposure, the stated reason, the daily asking-price history, and for buyers the label-sourced buyer fields (financing, lease, rent, real estate, inventory and FF&E included, training, franchise), the deal metrics (multiple vs its industry median with n, earnings yield, payback years) and the AI-read fields with their evidence quotes and gate status. Parameters: slug.
• get_mainstreet_coverage - Coverage per listing site and country: advertised versus scraped, disclosure rates, cross-site duplicates counted once, and each site's classification accuracy gate. Parameters: source, country.
• rank_mainstreet_industries_for_buyers - Industries ranked for buyers by Buyer Fit, a pre-registered score from asking-price economics and listing supply, computed within one currency and earnings basis (USD/SDE by default). Each row carries the score, its rank and every input with n: median earnings yield and multiple, median asking price, margin, years in operation, revenue per employee, healthy-exit share, seller-financing and owned-real-estate shares, and listings for sale. Groups with under 10 rankable industries (UK, AU, CA today) are withheld with the reason. Asking figures, not closed deals. Parameters: currency, earnings_basis, min_median_price, max_median_price, sector, limit, include_withheld.

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