Primateintelligence MCP

Name: Primateintelligence MCP
Author: Primate-Intelligence

by Primate-Intelligenceversion 0.4.0i★ –iComputer or cloud

Registry nameai.primateintelligence/mcp

Install

Overview

Description from the maker (original English)

Video scene understanding for AI agents via the Primate Vision API.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Computer or cloud
Transport: stdio, Streamable HTTP
Category: Design, images & audio
You need to fill in: PRIMATE_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on the maker’s server: what you ask it goes through their server.
You fill in yourself: PRIMATE_API_KEY, Authorization

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

Runs in the cloudNothing to install; it connects over the internet
npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Or run it on your computer

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "primateintelligence": {
      "command": "npx",
      "args": [
        "-y",
        "@primate-intelligence/mcp"
      ],
      "env": {
        "PRIMATE_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add --transport http primateintelligence https://api.primateintelligence.ai/mcp --header 'Authorization: Bearer {PRIMATE_API_KEY}'

Or run it on your computer

claude mcp add primateintelligence --env PRIMATE_API_KEY=your-value -- npx -y @primate-intelligence/mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "primateintelligence": {
      "url": "https://api.primateintelligence.ai/mcp",
      "headers": {
        "Authorization": "Bearer {PRIMATE_API_KEY}"
      }
    }
  }
}

Or run it on your computer

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "primateintelligence": {
      "command": "npx",
      "args": [
        "-y",
        "@primate-intelligence/mcp"
      ],
      "env": {
        "PRIMATE_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "primateintelligence": {
      "type": "http",
      "url": "https://api.primateintelligence.ai/mcp",
      "headers": {
        "Authorization": "Bearer {PRIMATE_API_KEY}"
      }
    }
  }
}

Or run it on your computer

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "primateintelligence": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@primate-intelligence/mcp"
      ],
      "env": {
        "PRIMATE_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

PRIMATE_API_KEY secret required env
Primate Vision API key (get a free one at https://primateintelligence.ai/docs/agents)
Authorization HTTP header

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain primateintelligence.ai (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
… Not checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
… Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Design, images & audioi

More stars than 0% of the other 2166 servers in this category
Published to the registry more recently than 20% of the other 2166 servers in this category
Basic checks equal to or better than 100% of the other 2166 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Primateintelligence MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: PRIMATE_API_KEY

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.4.0) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 16,165MITUpdated 5 months ago

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Figma MCP Server

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Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

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Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

@primate-intelligence/mcp

MCP (Model Context Protocol) server for the Primate Vision video analysis API — a video understanding API by Primate Intelligence (docs · llms.txt).

Gives AI agents video scene understanding as tools: register a video, ask a question in plain English, get a deterministic answer with a confidence score and clip timestamps. No hallucinated descriptions — the answer is yes / no / indeterminate with evidence.

Try it for free

A free test key requires no email, no card, no signup:

curl -X POST https://api.primateintelligence.ai/v1/sandbox

Your AI agent can do this for you — right from Claude. Point it at primateintelligence.ai/llms.txt and it can discover, provision, integrate, and self-verify with zero human steps.

Two ways to connect

1. Remote server (recommended) — OAuth, nothing to install

Streamable HTTP endpoint with full OAuth 2.1 + Dynamic Client Registration + PKCE:

https://api.primateintelligence.ai/mcp

In Claude.ai / Claude Desktop: Settings → Connectors → Add custom connector, paste the URL, sign in. No API key handling — the OAuth flow issues and rotates tokens for you.

2. Local stdio server

// claude_desktop_config.json · .mcp.json · mcp.json · .cursor/mcp.json

{ "mcpServers": { "primate-intelligence": { "command": "npx", "args": ["-y", "@primate-intelligence/mcp"], "env": { "PRIMATE_API_KEY": "pv_live_…" } } } }

Tools

Tool	Does	Read-only
`create_video_from_url`	Register a video from a public https URL (`POST /v1/videos`)	—
`create_analysis`	Ask a question about a video (`POST /v1/analyses`)	—
`validate_analysis`	Dry-run a prompt: assessability + cost estimate, zero credits (`validate_only: true`)	✓
`create_analysis_batch`	2–10 prompts on one video; each after the first billed at 50% (`POST /v1/analyses/batch`)	—
`get_analysis`	Fetch analysis status/result (`GET /v1/analyses/{id}`)	✓
`wait_for_analysis`	Poll until terminal state; returns `{ analysis, retry }`	✓
`list_models`	List available models (`GET /v1/models`)	✓
`get_usage`	Credit balance + period meters (`GET /v1/usage`)	✓
`get_credits`	Balance + per-analysis transaction ledger (`GET /v1/credits`)	✓
`get_test_fixture`	Stable fixture for integration self-verification (`GET /v1/test-fixture`)	✓

Every tool carries MCP annotations (title, readOnlyHint, destructiveHint, idempotentHint, openWorldHint), declares an outputSchema, and returns structuredContent conforming to it. No tool deletes data. Tool descriptions and schemas mirror the OpenAPI document at GET /v1/openapi.json — the spec is the source of truth.

Typical agent flow

get_test_fixture → verify the integration works (test keys return deterministic results, no quota burn)
create_video_from_url with the video URL
validate_analysis → confirm the prompt is assessable + preview estimated_cost_usd (free)
create_analysis with the question — *"Is there a person in this video?"* — or create_analysis_batch for several
wait_for_analysis → result.answer (yes | no | indeterminate) + result.confidence + result.clips + result.detected_count (count queries) + result.indeterminate_reason
On insufficient_credits: call get_credits, report the balance + recent debits, point the human at billing

Security contract

The API key is read from the PRIMATE_API_KEY environment variable only. No tool accepts a key, token, or secret as an argument — so credentials never land in agent transcripts, tool-call logs, or model context. This is enforced by a unit test that fails the build if any tool schema grows a credential-shaped parameter.

Errors surface the machine-readable error code, a docs_url, and the request_id so an agent can self-correct without a human in the loop.

Configuration

Var	Required	Default
`PRIMATE_API_KEY`	yes	—
`PRIMATE_BASE_URL`	no	`https://api.primateintelligence.ai`

Development

npm install

npm test # vitest — tool surface, security contract, polling, error shape npm run build # tsc → dist/

Primateintelligence MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Or run it on your computer

Or run it on your computer

Or run it on your computer

Or run it on your computer

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

@primate-intelligence/mcp

Try it for free

Two ways to connect

1. Remote server (recommended) — OAuth, nothing to install

2. Local stdio server

Tools

Typical agent flow

Security contract

Configuration

Development

Links

License