Primate Intelligence

SSE

by primate-intelligence

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GitHub Website SSE

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About

Real-time video analysis for AI agents — submit a video URL, ask a question in plain English, get a deterministic yes/no answer with confidence score and clip timestamps.

Details

Transport: SSE

Explore

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Primate Intelligence

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

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

JSON

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

JSON

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

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

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

JSON

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

JSON

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

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

From the repository

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

// claude_desktop_config.json · .mcp.json · mcp.json · .cursor/mcp.json { "mcpServers": { "primate-intelligence": { "command": "npx", "args": ](https://primateintelligence.ai/llms.txt)["-y", "@primate-intelligence/mcp"], "env": { "PRIMATE_API_KEY": "pv_live_…" } } } }

Every tool carries MCP annotations (title,readOnlyHint,destructiveHint,idempotentHint,openWorldHint), declares anoutputSchema, and returnsstructuredContentconforming to it. No tool deletes data. Tool descriptions and schemas mirror the OpenAPI document atGET /v1/openapi.json— the spec is the source of truth.
- get_test_fixture→ verify the integration works (test keys return deterministic results, no quota burn)
- create_video_from_urlwith the video URL
- validate_analysis→ confirm the prompt is assessable + previewestimated_cost_usd(free)
- create_analysiswith the question —"Is there a person in this video?"— orcreate_analysis_batchfor several
- wait_for_analysis→result.answer(yes|no|indeterminate) +result.confidence+result.clips+result.detected_count(count queries) +result.indeterminate_reason
- Oninsufficient_credits: callget_credits, report the balance + recent debits, point the human at billing

The API key is read from thePRIMATE_API_KEYenvironment 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 errorcode, adocs_url, and therequest_idso an agent can self-correct without a human in the loop.

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

- Quickstart for AI agents— the zero-human-intervention integration path
- API docs
- OpenAPI 3.1 spec
- Error registry
- llms.txt— machine-readable index for agents
- Privacy policy·Terms

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Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

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

McpServers

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

Transport

"stdio"

Package

"@primate-intelligence/mcp"

Registry

"npm"

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

Gives AI agentsvideo scene understandingas 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 isyes/no/indeterminatewith evidence.

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.txtand it can discover, provision, integrate, and self-verify with zero human steps.

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

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

// 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_…" } } } }

Errors surface the machine-readable errorcode, adocs_url, and therequest_idso an agent can self-correct without a human in the loop.

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