~/agentstafferAgentStaffer
Find, trial, compare, and govern AI agents before hiring
Roles / Technical Category
Review matching candidates
Next best action: Open a profile, compare evidence, then run a sandbox trial
MCP & Tool Integration
MCP servers, tool-use layers, SDK adapters, and integrations that connect agents to external tools.
4993total
4993filtered
238page
417pages
Category fit
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
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
backlog-md skill by nickcrew/claude-cortex
This skill helps agents manage backlog tasks with structured filing, prioritization, and progress tracking using Backlog.md CLI.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
bagman skill by openclaw/skills
This skill securely manages secrets and session keys for AI agents, preventing leakage and enabling safe, auditable wallet and API access.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
bags skill by openclaw/skills
This skill helps you manage Solana token launches, claim fees, and collaborate with agents or humans through Bags platform.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
bangai-recruit skill by openclaw/skills
This skill helps you manage Bang.AI recruitment tasks by viewing agents, filtering candidates, approving or rejecting applicants, and creating new agents.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
basal-ganglia-memory skill by openclaw/skills
This skill helps AI agents form automatic preferences and procedural memory by tracking habits, rewarding effective patterns, and refining workflows.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
batch-processing skill by willsigmon/sigstack
This skill helps you process many items efficiently using batch methods like agents, API batch, or loops across tasks.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
beepctl skill by blqke/beepctl
This skill lets you manage cross-platform messaging from the terminal, enabling AI agents to search chats, send messages, and control conversations via Beeper.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
belief-markets skill by openclaw/skills
This skill enables autonomous agents to trade on Belief Markets with automated NAV tracking, risk checks, and ledgered state for fully hands-off operation.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review support
Open Category guide
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.
Category guideTechnical role guideAgent inventoryResource mapReview guideAPI referenceSite contextSitemapProfile resources
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.
Review route: OpenAI review tools can start with openai.json; otherwise use site context and agent inventory before opening the finalist's complete review materials before install, hire, or promotion.