Benchwarmers
Related Servers
Alternatives to Benchwarmers
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceEnables orchestrating a panel of frontier AI models that independently propose, critique, revise, and converge on a single agreed answer to a problem, using existing vendor subscriptions or API keys.24 npm1MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that queries a panel of LLMs from different providers via OpenRouter and returns their answers side by side, optionally synthesizing them to highlight disagreements.1 npm1MIT
- AlicenseAqualityAmaintenanceBlind multi-model councils with anonymous LLM seats and direct 1:1 chat as a local MCP server. Enables asking one question to get independent answers from multiple model CLIs, then blind scoring and reveal.17AGPL 3.0
- FlicenseNot gradedqualityAmaintenanceEnables coding agents and OpenAI- or Anthropic-compatible clients to send chat requests through a single local pooled endpoint that spans free provider tiers, with keyless startup, automatic failover, model discovery, and capacity/health inspection tools.-
- AlicenseNot gradedqualityBmaintenanceSelf-hosted MCP gateway that aggregates many MCP servers into a single endpoint for AI clients, supporting hosted, local stdio, and Git-sourced MCPs.2MIT
- AlicenseNot gradedqualityDmaintenanceA self-hostable MCP server that routes prompts to multiple LLM providers using declarative policies, with multi-role orchestration for independence and verification.MIT
TDQS
Scored across 4 tools
Each tool targets a distinct step: discover collections, query a panel, submit a judgement, and enumerate unjudged seats. The only soft boundary is between `verdict` and `pending_verdicts`, which the description partially resolves by telling the agent it never needs to call the latter, though that still invites hesitation.
`list_collections` uses a verb_noun pattern while `ask` and `verdict` are bare action words and `pending_verdicts` is a noun phrase. The names are readable and memorable, but there is no single predictable convention an agent can rely on.
Four tools is lean but matches the narrow discover→ask→judge loop, with no redundant entries. `pending_verdicts` exists mainly for a plugin hook rather than agent use, so the effective agent-facing surface is even smaller, which is acceptable but slightly thin.
The core lifecycle is covered: enumerate collections, fan a prompt to all seats, and record per-seat correctness feedback that feeds routing. Gaps are minor: no way to inspect prior calls or verdicts, cancel a long-running `ask`, or query the 'confidently wrong' record that verdicts supposedly populate.