ProofBase MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ProofBase MCP Server Generate a professional testimonial for a CRM from a Sales VP who saved 10 hours a week"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ProofBase MCP Server
An MCP (Model Context Protocol) server for generating realistic customer testimonials using AI. Part of the ProofBase testimonial management ecosystem.
Features
AI-Powered Generation: Uses Claude to create authentic-sounding testimonials
Customizable Tone: Choose between professional, casual, or enthusiastic styles
Flexible Output: Includes customer name, role, company, avatar, and rating
Metric Support: Optionally include specific metrics for credibility
Installation
npm install proofbase-mcpOr install from source:
git clone <repo>
cd mcp-servers/proofbase-mcp
npm install
npm run buildConfiguration
Set your Anthropic API key:
export ANTHROPIC_API_KEY=your-key-hereUsage with Claude Desktop
Add to your Claude Desktop configuration (claude_desktop_config.json):
{
"mcpServers": {
"proofbase": {
"command": "node",
"args": ["/path/to/proofbase-mcp/dist/index.js"],
"env": {
"ANTHROPIC_API_KEY": "your-key-here"
}
}
}
}Available Tools
generate_testimonial
Generate a realistic customer testimonial.
Inputs:
Parameter | Type | Required | Description |
| string | ✅ | Name of the product |
| string | ✅ | Type of customer (e.g., "SaaS founder", "Marketing manager") |
| string | ✅ | Key benefit to highlight (e.g., "increased conversions") |
| string | ❌ | One of: "professional", "casual", "enthusiastic" (default: professional) |
| boolean | ❌ | Whether to include specific numbers (default: true) |
Example Output:
{
"name": "Sarah Chen",
"role": "Head of Marketing",
"company": "Flowstate",
"avatar": "SC",
"text": "ProofBase completely transformed how we showcase customer love. Our conversion rate jumped 34% after adding the wall of love to our landing page.",
"rating": 5
}Example Usage
User: Generate a testimonial for ProofBase from a startup founder who saw increased conversions
Tool Call: generate_testimonial
{
"product_name": "ProofBase",
"customer_type": "startup founder",
"outcome": "increased conversions",
"tone": "enthusiastic"
}
Result:
{
"name": "Marcus Johnson",
"role": "Founder & CEO",
"company": "Launchpad.io",
"avatar": "MJ",
"text": "Game-changer! We added ProofBase testimonials to our landing page and saw a 47% lift in signups within the first week. The setup was ridiculously easy.",
"rating": 5
}Development
# Install dependencies
npm install
# Run in development mode
npm run dev
# Build for production
npm run build
# Run tests
npm testTesting
# Run unit tests
npm test
# Test the server manually
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | node dist/index.jsLicense
MIT
Available Tools
1 toolgenerate_testimonialA
Generate a realistic customer testimonial for a product. Creates a fictional but believable testimonial with customer details, suitable for social proof.
Inputs: product_name (required), customer_type (required), outcome (required), tone, +1 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined and distinct by default.
A single tool inherently has consistent naming, as there are no other tools to compare against. The name 'generate_testimonial' follows a clear verb_noun pattern.
One tool is too few for a server named 'ProofBase MCP Server', which suggests a broader scope related to social proof or testimonials. A single tool feels thin and limited for this apparent domain.
The server's name implies a domain of social proof or testimonials, but with only a generation tool, there are significant gaps. Missing operations like retrieving, updating, deleting, or managing testimonials make the surface severely incomplete for the inferred purpose.
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