goai
GoAI is a Go library that provides a unified, type-safe interface for working with multiple LLM providers (OpenAI, Anthropic Claude, AWS Bedrock), generating vector embeddings, and performing similarity search using vector storage (including PostgreSQL vector storage). It also claims support for streaming and provides a documented Model Context Protocol (MCP) server for Go.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
No specific security controls are described in the README beyond pointing to a Security Policy. Authentication appears to rely on provider API keys supplied by the application (likely via environment variables as shown), but the README does not state how secrets are handled internally (e.g., logging redaction) or whether the library supports scoped/least-privilege credentials.
⚡ Reliability
Best When
You are building a Go application and want a single abstraction over several LLM providers plus embeddings/vector search, with an emphasis on developer experience (consistent interfaces and streaming).
Avoid When
You need a server-side managed platform with documented uptime/SLA, rate-limit guarantees, and centralized auth/authorization controls independent of upstream providers.
Use Cases
- • Building Go applications that use multiple LLM providers behind a consistent interface
- • Generating text embeddings and storing them for semantic search
- • Implementing retrieval/similarity search pipelines using PostgreSQL vector storage
- • Streaming LLM responses in chat or assistant-style applications
- • Providing an MCP server for model-context tooling integration
Not For
- • Use as a standalone hosted API (it is a library, not a managed service)
- • Workloads requiring guaranteed enterprise reliability/SLA documentation from the library maintainers
- • Environments where you cannot supply provider credentials (API keys) to the underlying LLM providers
Interface
Authentication
Authentication is delegated to the underlying LLM provider clients (e.g., API keys). The README does not describe OAuth flows or fine-grained scopes at the library layer.
Pricing
The library itself is MIT-licensed (no pricing described here), but actual costs depend on the selected LLM/vector provider usage.
Agent Metadata
Known Gotchas
- ⚠ Authentication is provider-specific; agent must know which underlying provider client/config to use.
- ⚠ Operational concerns like rate limits and retry/backoff likely need to be implemented with provider behaviors in mind; library-level guidance is not shown in the provided README.
Alternatives
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Scores are editorial opinions as of 2026-04-04.