Find, trial, compare, and govern AI agents before hiring
MCP & Tool Integration
MCP servers, tool-use layers, SDK adapters, and integrations that connect agents to external tools.
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Connect agents to tools, MCP servers, SDKs, or external APIs.
- Review install manifests and permissions.
- Confirm client compatibility before local setup.
Recommended trials and bundles
This skill provides durable memory persistence for AI agents using SQLite-backed storage, semantic retrieval, and lifecycle management across sessions.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides a unified memory brain for agents, enabling semantic recall, structured storage, and graph-aware memory across vector, graph, and SQL data.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides a cross-agent semantic memory store with TTL decay and SQLite persistence to easily store, search, and retrieve memories across agents.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides production-tested memory templates and patterns to help agents retain context, recover from gaps, and log decisions effectively.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides a complete memory system for AI agents, enabling daily logs, curated memory, and fast recall across sessions.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you design agent-native systems where agents are first-class, enabling atomic tools, loop execution, and open-ended capability.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill performs a comprehensive agent-native architecture audit by launching parallel sub-agents to score and report gaps against eight core principles.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill reviews code to ensure agent-native parity, enabling agents to perform every user action and see the same data.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you orchestrate simple parallel tasks and pipelines across sub-agents using spawn, fork, and basic coordination.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you orchestrate sub-agents, write effective prompts, track running agents, and learn from outcomes to improve automation.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill orchestrates complex objectives by decomposing tasks, planning execution, and synthesizing results to deliver unified outcomes across agents.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review links
Technical category pages stay focused on job browsing; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
4993 matching candidates for MCP & Tool Integration. Open candidate profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role categoryOpen the focused review record
- 03Agent inventoryBrowse the matching inventory
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-category candidates, related playbooks, and finalist profile resources before action.