mcp-builder

mcp-builder is an agent for Claude Code from nobrainer-tech/langflow-mcp. It costs 61 tokens per session (2,865 once invoked), scanned A, original, MIT.

A guide for building MCP servers, which let AI agents use tools that connect to outside services and APIs.

In plain words
What is it for?
Plan and build MCP servers in Python or TypeScript, including tools for APIs, databases, and other external services.
Why use it?
It helps turn an external service into tools that support complete tasks, while keeping responses focused and the integration practical for an agent's limited context.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/nobrainer-tech/langflow-mcp/mcp-builder
Clone the repo
git clone --depth 1 https://github.com/nobrainer-tech/langflow-mcp

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mcp-builder

README.md
[![agentmods](https://agentmods.dev/badge/agents/nobrainer-tech/langflow-mcp/mcp-builder.svg)](https://agentmods.dev/agents/nobrainer-tech/langflow-mcp/mcp-builder)
Your own site
<a href="https://agentmods.dev/agents/nobrainer-tech/langflow-mcp/mcp-builder"><img src="https://agentmods.dev/badge/agents/nobrainer-tech/langflow-mcp/mcp-builder.svg" alt="Measured on agentmods" height="20"></a>
Per session 61 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,865 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00061 $0.02865
Opus 5 $0.00030 $0.01432
Sonnet 5 $0.00012 $0.00573
Haiku 4.5 $0.00006 $0.00286

Measured 4d ago against content hash b1010e90adcb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp-builder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/mcp-builder.md · 329 lines

How it starts

The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MCP Server Development Guide

Overview

To create high-quality MCP (Model Context Protocol) servers that enable LLMs to effectively interact with external services, use this skill. An MCP server provides tools that allow LLMs to access external services and APIs. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks using the tools provided.


Process

🚀 High-Level Workflow

Creating a high-quality MCP server involves four main phases:

Phase 1: Deep Research and Planning

1.1 Understand Agent-Centric Design Principles

Before diving into implementation, understand how to design tools for AI agents by reviewing these principles:

Build for Workflows, Not Just API Endpoints:

  • Don't simply wrap existing API endpoints - build thoughtful, high-impact workflow tools
  • Consolidate related operations (e.g., schedule_event that both checks availability and creates event)
  • Focus on tools that enable complete tasks, not just individual API calls
  • Consider what workflows agents actually need to accomplish

Optimize for Limited Context:

  • Agents have constrained context windows - make every token count
  • Return high-signal information, not exhaustive data dumps
  • Provide "concise" vs "detailed" response format options
  • Default to human-readable identifiers over technical codes (names over IDs)
  • Consider the agent's context budget as a scarce resource

Design Actionable Error Messages:

  • Error messages should guide agents toward correct usage patterns
  • Suggest specific next steps: "Try using filter='active_only' to reduce results"
  • Make errors educational, not just diagnostic
  • Help agents learn proper tool usage through clear feedback

Follow Natural Task Subdivisions:

  • Tool names should reflect how humans think about tasks
  • Group related tools with consistent prefixes for discoverability
  • Design tools around natural workflows, not just API structure

Use Evaluation-Driven Development:

  • Create realistic evaluation scenarios early
  • Let agent feedback drive tool improvements
  • Prototype quickly and iterate based on actual agent performance

Read the full file on GitHub · 329 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 329 lines · 61 tokens per session scan A b1010e90adcb

Subscribe to this mod's changes

mcp-builder is an agent published in the GitHub repository nobrainer-tech/langflow-mcp (10 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 2,865 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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