agent-swarm.devGuides
Provider Capability Matrix
What each install-time LLM provider supports, and which optional keys unlock missing features
The provider you choose during onboarding selects the worker harness and its model credentials. Some server-side features use a separate internal LLM or embedding credential, so a worker can run successfully while those features remain off. Without an embedding key, keyword-based full-text memory search still works, but semantic and hybrid ranking do not.
| Install choice | Memory search | Session summaries + memory rating | Workflow LLM nodes (raw-llm / validate) | Task steering | Session-end profile sync | Skills directory | MCP wiring | Structured output | Reasoning effort | Spend tracking | Rate-limit handling | Model-tier mapping |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Claude Code | Semantic/hybrid search with OPENAI_API_KEY or EMBEDDING_API_KEY | Yes; LLM rating when enabled | Needs OPENAI_API_KEY or OPENROUTER_API_KEY; Claude-only credentials are not supported | Queue at turn boundaries | Yes | Native, ~/.claude/skills | Yes | Yes | Model-dependent | Yes | Structured reset times | Yes |
| OpenAI / Codex | Semantic/hybrid search with OPENAI_API_KEY or EMBEDDING_API_KEY | Yes; LLM rating when enabled | Yes with OPENAI_API_KEY | Queue via managed Codex hooks | Yes | Inline resolver, ~/.codex/skills | Yes | Yes | Model-dependent; Codex also supports max on capable models | Yes | Structured API limits and credits cooldown | Yes |
| OpenRouter via pi | Semantic/hybrid search with OPENAI_API_KEY or EMBEDDING_API_KEY | Yes; LLM rating when enabled | Yes | Live steer and queued follow-up | Yes | Native, ~/.pi/agent/skills | Yes | Yes | Model-dependent | Yes | Flat five-minute cooldown | Yes |
| AWS Bedrock via pi (alpha) | Semantic/hybrid search with OPENAI_API_KEY or EMBEDDING_API_KEY | No with Bedrock credentials alone | No with Bedrock credentials alone | Live steer and queued follow-up | Yes | Native, ~/.pi/agent/skills | Yes | Yes | Model-dependent via pi | No; Bedrock models are unpriced | pi retries; AWS throttles get actionable retry guidance, but no runner credential cooldown | No built-in mapping; pi defaults point to OpenRouter models |
How to unlock missing features
- Semantic memory search, every provider: set
OPENAI_API_KEYor the dedicatedEMBEDDING_API_KEYon the API server. - Workflow LLM nodes with Claude-only or Bedrock-only credentials: set
OPENAI_API_KEYorOPENROUTER_API_KEYon the API server. - Bedrock session summaries and memory rating: set
OPENAI_API_KEYorOPENROUTER_API_KEYfor the internal AI credential chain. Native Bedrock support is not available yet. - Bedrock model tiers: set
MODEL_TIER_SMOL,MODEL_TIER_REGULAR,MODEL_TIER_SMART, andMODEL_TIER_ULTRA, or provide the same mappings throughMODEL_TIER_MAP, using reachableamazon-bedrock/...model IDs. - Bedrock spend tracking and runner credential cooldowns: no environment variable unlocks these today; they remain alpha limitations.
Alpha: session summaries, memory rating, spend tracking and model tiers may be missing on Bedrock.
For provider credentials and model selection, see Harness Configuration. For implementation details behind this matrix, see Adding a Harness Provider.