Agent Capability Matcher Connector for AI agents.
3 live capabilities
Optimize multi-agent delegation with precise skill scoring
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Why people use Agent Capability Matcher
Stop agent delegation errors with Agent Capability Matcher
With this MCP, you turn that guesswork into a math problem. You can instantly see which agent is the most qualified for a job before the task is ever sent. You get a clear, data-driven way to route work, making your entire multi-agent system feel much more stable and predictable.
What Vinkius changes
You stop wasting resources on the wrong agents by using data to prove who is actually capable of doing the work.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Automated Task Routing
An orchestration agent uses query_agent_matches to decide whether to send a coding task to a Python specialist or a web-search specialist.
- Real-world use case 02
Agent Fleet Auditing
An engineer uses verify_capability_gap to figure out why a specific agent keeps failing at data visualization tasks.
- Real-world use case 03
Custom Scoring Logic
A developer uses calculate_match_metrics to build a custom, weighted selection algorithm for a highly specialized industry.
Complete set · 3capabilities
The complete Agent Capability Matcher capability set.
These are the exact actions your AI can choose when you ask it to work with Agent Capability Matcher.
01—03
3 capabilities in this set.
Part of 3 available through Agent Capability Matcher.
- 01 Capability
Calculate match metrics
Retrieves the raw mathematical components of a match without the final weighted aggregation. This gives you the underlying data for custom scoring.
- 02 Capability
Query agent matches
Ranks all available agents against a specific task to find the best candidate. It helps you pick the winner from a crowd of options.
- 03 Capability
Verify capability gap
Performs a deep-dive check on a single agent to see exactly what is missing for a specific task. Use this to find out why an agent is failing.
Set up in minutes
One URL. Then ask Agent Capability Matcher to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Agent Capability Matcher from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ksBlmiSpAX79YJ4qEqyAk4ehNCsTLaukhvhpCJ0H/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Agent Capability Matcher, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Agent Capability Matcher for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ksBlmiSpAX79YJ4qEqyAk4ehNCsTLaukhvhpCJ0H/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Agent Capability Matcher URL.
- Step 03
Save and start
Save the connection and enable Agent Capability Matcher in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-capability-matcher": {
"url": "https://edge.vinkius.com/vk_preview_ksBlmiSpAX79YJ4qEqyAk4ehNCsTLaukhvhpCJ0H/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Agent Capability Matcher
Open Agent mode in chat and ask: "Using Agent Capability Matcher, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-capability-matcher": {
"url": "https://edge.vinkius.com/vk_preview_ksBlmiSpAX79YJ4qEqyAk4ehNCsTLaukhvhpCJ0H/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Agent Capability Matcher
Ask Copilot: "Using Agent Capability Matcher, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-capability-matcher": {
"url": "https://edge.vinkius.com/vk_preview_ksBlmiSpAX79YJ4qEqyAk4ehNCsTLaukhvhpCJ0H/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Agent Capability Matcher
Open Cascade and ask: "Using Agent Capability Matcher, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-capability-matcher": {
"url": "https://edge.vinkius.com/vk_preview_ksBlmiSpAX79YJ4qEqyAk4ehNCsTLaukhvhpCJ0H/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Agent Capability Matcher
Ask Cline: "Using Agent Capability Matcher, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add agent-capability-matcher --transport http "https://edge.vinkius.com/vk_preview_ksBlmiSpAX79YJ4qEqyAk4ehNCsTLaukhvhpCJ0H/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Agent Capability Matcher
Ask Claude: "Using Agent Capability Matcher, show me...". 3 tools are ready
Where the request belongs
Work Agent Capability Matcher can move forward.
This is for engineers and architects building complex, multi-agent systems who are tired of unpredictable agent performance and failed task delegations.
AI Orchestration Engineer
Designing the logic that decides how tasks move between different specialized agents.
LLM Ops Specialist
Monitoring agent performance and identifying where to add new capabilities or skills to the fleet.
Multi-Agent System Architect
Building the structural framework for autonomous agent swarms that require high reliability.
Build the capability set
Add more capabilities.
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Bring your own AI
Change the model, client or framework. Keep Agent Capability Matcher connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
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CrewAI -
Vercel AI SDK
Before you connect
Questions about Agent Capability Matcher.
The practical details behind the request, access and result.
How can Agent Capability Matcher help with my multi-agent system?
It provides a way to mathematically score how well an agent fits a task, ensuring you delegate to the right agent every time.
Can I use Agent Capability Matcher to find out why an agent is failing?
Yes, you can use it to audit specific agents and identify exactly which skills or capabilities they are missing for a given task.
Does Agent Capability Matcher work with any AI client?
Yes, as long as your client is MCP-compatible, like Claude, Cursor, or Windsurf, you can use this to manage your agents.
How does Agent Capability Matcher decide which agent is best?
It calculates a score by looking at how many required skills overlap with the agent and whether the agent has the necessary capabilities to complete the job.
Can I see the math behind the Agent Capability Matcher scores?
Yes, you can pull the raw skill and capability metrics to see exactly how the final capability score was calculated.
How is the capability score calculated?
The score is a weighted combination: 60% for skill keyword overlap (Jaccard similarity) and 40% for capability coverage ratio.
Can I see exactly what an agent is missing?
Yes, by using the verify_capability_gap capability, you can retrieve a list of specific missing skills and capabilities for a given agent profile.
What happens if no agents match the task?
The system handles empty profiles or requirements gracefully, returning empty results or zero scores without errors.
One connection away
Give your agent a direct line to Agent Capability Matcher.
Connect Agent Capability Matcher once. Keep it beside 6,100+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available