{"id":"blueman82-ai-counsel","name":"ai-counsel","af_score":57.0,"security_score":28.8,"reliability_score":27.5,"what_it_does":"AI Counsel is a self-hostable MCP server that runs multi-participant, multi-round “deliberation” among AI models to debate, cast structured votes with confidence/rationale, and converge on a decision. It can optionally ground decisions using evidence-based tools (read/search/list/run safe commands) against a provided working directory, includes transcript/audit outputs, and can reuse context via semantic retrieval of past debates.","best_when":"You want a programmable, repeatable consensus process (with audit transcripts) and optional evidence grounding on local code/data using self-hosted model runners (or configurable cloud adapters), and you can configure tool security/working directory carefully.","avoid_when":"You cannot configure or enforce tool access boundaries (working_directory, exclude_patterns, command whitelist) and you need to prevent any file/command exposure; also avoid when you need formal compliance guarantees without further evaluation.","last_evaluated":"2026-03-30T13:37:30.512280+00:00","has_mcp":true,"has_api":false,"auth_methods":[],"has_free_tier":false,"known_gotchas":["Evidence/tooling requires correct working_directory; misconfiguration leads to file-not-found errors.","Some adapters have weaker isolation (README states Codex may access any file and Ollama/LMStudio have no file system access restrictions since they are HTTP adapters).","Tool security must be configured (exclude_patterns, max_file_size_bytes, command_whitelist) to reduce risk.","Local adapter reliability depends on the external runner (Ollama/LM Studio/others) and model availability.","Model output formatting/structured votes may degrade for small models (<3B mentioned as not recommended)."],"error_quality":0.0}