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Foundersignal MCP Server

@carlosalvite

Repository

Basic information

Category

Other

Transports

stdio

Author

carlosalvite

Submitted by

Carlos Alvite

About Foundersignal MCP Server

Ask Claude what SaaS ideas are worth building. Pulls revenue data, growth signals and community pain points from AppSumo, TrustMRR, Product Hunt, Indie Hackers, Reddit and more — and returns a ranked list of opportunities in seconds.

#saas#market-research#founder-tools#indie-hackers#claude#ai-tools#idea-finder

Foundersignal MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "foundersignal": {
      "command": "npx",
      "args": [
        "foundersignal-mcp"
      ]
    }
  }
}

Foundersignal MCP Server tools

4

Query FounderSignal's market intelligence database and return all ranked SaaS opportunities scored by revenue proof, competition density, momentum, and build feasibility. Returns structured JSON. Use this first, then write Market Gap / Why Now / Execution Plan narratives for each idea, then call render_report to produce the final HTML artifact.

Render the final personalized discovery report as a full HTML document. Pass the ideas array from get_discover_data, each augmented with a narrative object containing marketGap, whyNow, and executionPlan (written by you based on the data). Returns an HTML artifact to display directly.

Query aggregated market intelligence from TrustMRR, AppSumo, Product Hunt, Indie Hackers, Reddit and Google SERP. Returns a ranked text table of SaaS opportunities scored across revenue proof, momentum, entry window, pain intensity and build feasibility.

Generate a full HTML market intelligence report with all ranked opportunities.

Overview

What is Foundersignal?

FounderSignal is an MCP server that connects Claude to curated market intelligence. It lets users ask natural-language questions about SaaS categories, bootstrapped products, underserved niches, and competitive landscapes instead of manually collecting data from multiple sources.

How to use Foundersignal?

Add the server configuration to your MCP client’s mcpServers object using the command npx foundersignal-mcp. Then prompt Claude with market-research questions such as “What SaaS categories are growing fastest right now?” or “Show me bootstrapped products that hit $10K MRR in under a year.”

Key features of Foundersignal

  • Answers natural-language market-intelligence queries.
  • Returns ranked tables with revenue benchmarks and competition analysis.
  • Generates full HTML reports with 30 ranked ideas.
  • Aggregates data from 13+ public sources (AppSumo, Reddit, Crunchbase, etc.).
  • Early access via waitlist at foundersignal.io.

Use cases of Foundersignal

  • Identify fastest-growing SaaS categories.
  • Discover bootstrapped products reaching $10K MRR quickly.
  • Find underserved niches in the creator tools space.
  • Spot B2B categories with high demand and no clear winner.
  • Export a complete market intelligence report for offline review.

Frequently asked questions

1

What data sources does Foundersignal use?

It pulls from AppSumo, TrustMRR, Product Hunt, Indie Hackers, Reddit, Hacker News, G2, Exploding Topics, Google Trends, Crunchbase, LinkedIn, TikTok, and Meta Ads Library.

2

How can I get access to Foundersignal?

It is in early access. Join the waitlist at [foundersignal.io](https://05-founder-signal-landing.vercel.app).

3

What tools does Foundersignal expose?

Two tools: `market_query` (returns a ranked table of opportunities with revenue benchmarks, growth signals, and competition analysis) and `generate_report` (exports a full HTML market intelligence report to disk with 30 ranked ideas).

4

How do I install Foundersignal?

Add the following to your MCP client configuration: ```json { "mcpServers": { "foundersignal": { "command": "npx", "args": ["foundersignal-mcp"] } } } ```

5

Are there any limitations in the early access?

The README does not specify limitations beyond requiring a waitlist signup. Data source coverage and report generation are outlined, but exact query limits or runtime requirements are not stated.

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