Primateintelligence

Install

Works with Claude Code, VS Code, Codex, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/primateintelligence-ai-mcp

About

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools

7 read · 3 write · 0 delete

Secrets

1 (API keys, tokens or passwords)

Install scripts

None found

Runs as

Node.js package

Tools (10)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• create_analysisAnalyze video

  Ask a question about a video (POST /v1/analyses). Provide video_id (video_…) and a free-text prompt like "Is there a person in this video?". Analysis runs asynchronously — use wait_for_analysis to block until done. The result contains answer (yes|no|indeterminate), confidence (0-1), clip timestamps, detected_count (count queries), and indeterminate_reason. Recommended: call validate_analysis first to confirm the prompt is assessable and preview the cost before spending credits. For 2–10 prompts on the same video, use create_analysis_batch (each prompt after the first is billed at 50%).

• create_analysis_batchAnalyze video with multiple prompts (batch discount)

  Run 2–10 prompts against the SAME video in one call (POST /v1/analyses/batch). Pricing: the first prompt is billed at full price, each additional prompt at 50% — always cheaper than separate create_analysis calls for multi-question workloads. Returns an analysis_batch with every analysis resource plus a pricing summary; poll each analysis id individually with get_analysis or wait_for_analysis. To check assessability of individual prompts first, use validate_analysis (free).

• create_video_from_urlIngest video from URL

  Register a video from a public https URL for analysis (POST /v1/videos, URL-ingest mode). The API fetches the video asynchronously — the returned video starts in status "processing" and becomes "ready". Supports video/mp4 and video/quicktime, max 2 GiB. Returns the video resource with its id (video_…).

• get_analysisGet analysis resultread-only

  Fetch an analysis by id (GET /v1/analyses/{id}). While running, shows live progress and queue_position. When status is "completed": result.answer (yes|no|indeterminate), result.confidence (for count queries this is confidence in the count itself), result.clips, result.detected_count (count-intent queries only; 0 = assessable but nothing found), result.indeterminate_reason (low_confidence — retry with a more specific prompt; nothing_detected — genuinely empty; unsupported_query_form — rephrase as yes/no or count; duration_mismatch — result untrusted), and result.video_duration_s (null when dura…

• get_creditsGet credit balance & transaction historyread-only

  Get the credit balance and transaction ledger for this API key (GET /v1/credits). Returns balance_seconds (the authoritative balance, in billable seconds), grant_seconds, used_seconds, and a paginated transaction list where each debit carries the analysis/stream id it came from (source_id, source_type). Use this to audit what each analysis cost, check the balance before a batch job, or diagnose an insufficient_credits error.

• get_test_fixtureGet test fixtureread-only

  Get the stable test fixture (GET /v1/test-fixture): a video URL + prompt + expected answer for verifying an integration end-to-end without burning quota. Test-mode (pv_test_) keys return deterministic canned results.

• get_usageGet usage & credit balanceread-only

  Get credit balance and period usage meters for the current API key (GET /v1/usage). Use this after an insufficient_credits error to report the balance. For the per-analysis transaction ledger (what each analysis cost, with source ids), use get_credits instead.

• list_modelsList analysis modelsread-only

  List available analysis models (GET /v1/models) with status (stable | preview | deprecated) and capabilities. Use the model marked default:true unless you have a reason not to.

• validate_analysisValidate prompt & preview cost (free)read-only

  Dry-run a prompt WITHOUT creating an analysis or spending credits (POST /v1/analyses with validate_only: true). Compiles the prompt and returns an analysis_preview: the compiled query, assessable (false means the model cannot score this query form — rephrase as a yes/no or count question), estimated_seconds, and estimated_cost_usd (both null when the video duration is not yet known). Recommended before create_analysis to catch unassessable prompts and preview cost.

• wait_for_analysisWait for analysis to finishread-only

  Block until an analysis reaches a terminal state (completed | failed | canceled), polling GET /v1/analyses/{id}. Returns { analysis, retry }: retry is null when the analysis reached a terminal state, or carries timeout guidance when the wait expired (call again). Default timeout 120s (test-mode analyses complete in seconds). On completion, see get_analysis for the full result field semantics (detected_count, indeterminate_reason, nullable video_duration_s, usage snapshot).

Signals

Stars

0

Forks

0

Open issues

0

Last commit

Aug 1, 2026 (2 months ago)

Last release

Aug 1, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name

ai.primateintelligence/mcp

Version

0.4.0

Auth

Bearer token, API key

Packages

npm @primate-intelligence/mcp

License

MIT

Repository

github.com/Primate-Intelligence/primate-intelligence-mcp

Website

primateintelligence.ai/docs/agents

First seen

Oct 24, 2026

Last checked

Oct 24, 2026

Source

Official MCP Registrygithub-graphql