Embedder

https://embedder.dev
52
Good (public checks)
Agent Native Score

Embedder is a service for generating and managing embeddings, providing APIs to convert text into vector representations for semantic search, similarity matching, and AI applications.

Categories: Ai · Embeddings · Nlp
#1 of 20 in Ai · #1 of 2 in Embeddings · #2 of 9 in Nlp
Checklist Breakdown

0 of 33 checks passed.

Discovery 45%

Can an agent find and understand this tool without a web search?

— Published OpenAPI/Swagger spec
— Has llms.txt or llms-full.txt
— Has an MCP server (official or well-maintained)
— MCP server listed in a public registry
— API reference docs are publicly accessible
— Docs include runnable code examples
— Has a public changelog or release notes
— Has a public status page
Auth & Onboarding Not yet scored

Can an agent create an account and get credentials without human intervention?

— Signup does not require CAPTCHA
— Signup does not require phone verification
— Supports API key auth (not only OAuth)
— API key obtainable without manual approval
— No mandatory billing info to start
— Can sign up without creating an organization
Pricing Not yet scored

Can an agent operate autonomously without upfront payment or contracts?

— Has a free tier
— Usage-based pricing available
— No minimum contract or commitment
— Pricing page is public (no 'contact sales')
— Free tier sufficient for testing (not just a trial)
Agent Tooling Requires account Not yet scored

How well does the API work for non-human consumers?

— SDK available in 2+ languages
— Structured error responses (JSON with error codes)
— Idempotency support on write endpoints
— Pagination on list endpoints
— Webhook/event support
— Sandbox or test mode available
— Rate limit headers in responses
— Consistent REST resource naming
Reliability Requires account 60%

Does the tool fail gracefully when an agent makes a mistake?

— Meaningful error messages (not just 500)
— 429 responses include Retry-After header
— Documented uptime SLA (99.9%+)
— Graceful degradation under rate limits
— Request IDs in responses for debugging
— API versioning supported
Reviewer Notes

Embedder provides a REST API with API key authentication and a free tier, making it reasonably accessible for agents. However, it lacks an MCP server and llms.txt file, limiting discoverability. Account creation requires human interaction (email verification), which blocks fully autonomous signup. The API is straightforward for embedding operations, but documentation could be more agent-friendly with clearer error codes and structured response examples. Reliability appears solid with reasonable rate limits, though specific uptime SLAs are not publicly documented.

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