Flight data for Spain's 50 AENA airports over the public and OAuth2 REST APIs.
MCP server for Atlassian Confluence Data Center - access and manage content.
MCP server for Atlassian Jira Data Center - search, view, and create issues.
Agent-first prediction markets on Base. Trade, quote, create markets via MCP.
Solana token safety for AI agents — rug-pull, honeypot & Token-2022 trap detection before you buy.
Search Console for agents: index status, unindexed-URL discovery, Request Indexing, sitemaps.
Structured-output enforcer: extract and validate JSON from messy LLM text.
Token-aware message truncation: fit a chat history into your model's context budget.
Network-egress firewall for agent tools: check URLs against a declarative policy.
Snapshot tests for AI tool-call traces: diff, validate, and catch silent regressions.
Validate tool-call args before execution. Returns LLM-friendly retry hints.
Inject, parse, and strip [N] citation markers in RAG outputs.
Token-budget-aware text handling: count, truncate, and chunk for LLM prompts.
Diagnose RAG drift: interpret scores, recommend thresholds, explain dimensions.
RAG retrieval IR metrics: recall@k, hit@k, MRR, NDCG@k, evaluate_batch.
Parse partial / truncated / messy JSON for LLM tool calls and structured outputs.
FIBER decision-context compiler with honest omission accounting: 259 evidence-bearing MCP tools.
Tells AI agents which files to test first — churn, coverage, and test mapping as risk scores.
Score sentiment toward specific entities in text. Cluster documents and name topics.
Fully local memory for AI agents: zero-LLM ingest, semantic recall, air-gapped, auditable.
Agent context flight recorder: restore after compaction, fan-out packs, signed git-bound receipts.
Search, compare, and get pricing for 8,600+ software tools with verified data.
Hierarchical markdown memory palace for AI agents — structured palace navigation via MCP tools.
Compare software: verified pricing with its source and date, and ranked alternatives.
About AI & Agents MCP servers
This category collects servers that make agents better at being agents. You will find orchestration layers that run multi-step pipelines, routers that hand a task to the right model or sub-agent, evaluation and tracing tools, prompt and skill libraries, and bridges that let one assistant call another. Some wrap commercial model APIs; others are thin coordination layers around open-source frameworks.
Because these servers often sit between your agent and other systems, look closely at where data flows and what is logged. Prefer servers that document their tool contracts clearly, support streaming where relevant, and can run locally when the workload is sensitive. Many are new and move quickly, so check the repository's recent activity before relying on one in production.