FounderBrain
See how a founder came across in a pitch or investor call, compared with 773 founder interviews.
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"founderbrain": {
"url": "https://mcp.thinkreasonlearn.com/mcp"
}
}
}Remote endpoints
https://mcp.thinkreasonlearn.com/mcpstreamable-httpWhat it can do
Tool inventory
Tools (2)
🟢analyse_transcript(transcript, speaker, name, role)
Compare one speaker in a meeting transcript with public founder and operator interviews and return the report as data: speaking type, style positions, similar well-known people, standout habits and takeaways. transcript: the whole text, one speaker turn per line ("Name: words"). speaker: one speaker label as it appears in the text. name: the person's name when the label is generic (Me, Them, Speaker 2), or "You" when the speaker is the user; required for a generic label other than Me. role: "answering" when they were pitching or answering questions, "asking" when they mostly asked them. Needs at least 300 words from the speaker and at most 15,000 words in all; usually takes under a minute, up to about two minutes when the service is starting up. Clients that support MCP Apps also show the visual report.
Input Schema
{
"type": "object",
"properties": {
"transcript": {
"default": "",
"title": "Transcript",
"type": "string"
},
"speaker": {
"default": "",
"title": "Speaker",
"type": "string"
},
"name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Name"
},
"role": {
"default": "answering",
"title": "Role",
"type": "string"
}
},
"title": "analyse_transcriptArguments"
}🟢check_transcript(transcript)
List the speakers in a meeting transcript and how many words each said, without scoring anything. transcript: the whole text, one speaker turn per line ("Name: words").
Input Schema
{
"type": "object",
"properties": {
"transcript": {
"default": "",
"title": "Transcript",
"type": "string"
}
},
"title": "check_transcriptArguments"
}Output Schema
{
"type": "object",
"additionalProperties": true,
"title": "check_transcriptDictOutput"
}Community
Evidence