Skip to content
TrustedSkillsbeta
Back to all skills

V3 Mcp Optimization

Checked
ruvnet·vlatest·agents·MIT

Helps with MCP tools, optimization as part of orchestrating AI agents and multi-step workflows workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it V3 MCP Optimization, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add ruvnet/ruflo --skill "V3 MCP Optimization" --full-depth -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

ruvnet

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned ruvnet/ruflo at b636802d8c.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
b636802d8c
Manifest
.agents/skills/v3-mcp-optimization/SKILL.md
Scanned
3 files, 2,253 lines
Copies in repo
3 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill optimizes claude-flow v3 Model Context Protocol (MCP) server implementations. It achieves this through advanced transport layer optimizations, connection pooling, load balancing, and comprehensive performance monitoring. The goal is to significantly reduce response times, aiming for sub-100ms performance. It addresses current issues like slow startup latency, connection overhead, inefficient tool registry lookups, lack of connection reuse, and high memory usage.

When to use it

  • When experiencing slow response times from your claude-flow v3 MCP server.
  • If you need to improve the performance and scalability of AI agent workflows relying on MCP tools.
  • To reduce startup latency for your MCP server.
  • When dealing with connection overhead issues in your MCP setup.

Key capabilities

  • Connection Pooling: Reuses existing connections to minimize overhead.
  • Load Balancing: Dynamically distributes requests across multiple instances.
  • Transport Layer Optimization: Improves the efficiency of data transmission.
  • Performance Monitoring: Tracks key metrics for ongoing optimization.
  • Tool Registry Optimization: Uses hash tables or tries for faster tool lookups (O(1) target).

Example prompts

  • "Analyze the current MCP server performance and identify bottlenecks."
  • "Implement connection pooling for the MCP tools."
  • "Add dynamic load balancing to handle increased MCP traffic."

Tips & gotchas

  • Requires a claude-flow v3 environment.
  • The skill aims for significant improvements in areas like startup time, tool lookup speed, and response time; however, actual results will depend on the existing infrastructure.
  • Configuration options (e.g., maxConnections, toolIndexType) are available to fine-tune performance based on specific needs.