MCP Server Architect
The default MCP server is an API wrapper that dumps forty endpoint-shaped tools on the model and hopes — and the model gets confused, picks the wrong tool, and produces garbage that looks like a tool call
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THE AGENSI STORE
355 skills found
The default MCP server is an API wrapper that dumps forty endpoint-shaped tools on the model and hopes — and the model gets confused, picks the wrong tool, and produces garbage that looks like a tool call
Transform fragile AI prototypes into resilient, enterprise-ready production agents with professional hardening tools.
Design, diagnose, and optimize high-performance RAG systems with an engineering-first framework.
Paste any AI output. Get the production-ready prompt that made it.
Audit any website for AI agent-readability via native MCP tool calls.
Production prompts grow by accretion — every failure gets another appended rule until the prompt is two thousand words of contradictions that the model navigates unpredictably
An adversarial gate that audits an MCP server or agent tool definition — schemas, descriptions, scopes, auth — for tool poisoning, excessive agency, injectable descriptions, and missing access controls, then returns one SAFE/REVIEW/BLOCK verdict.
Audit any website for AI agent-readability and protocol compliance using the Agent Ready CLI.
Optimize your website's architecture and content to be discovered, indexed, and cited by AI agents and LLMs.
Adversarial memory audit to remove PII, stale facts, and injected instructions from agent storage.
by Joker
Model selection matrix (MJ/Flux/SD), composition rules, 3-level quality gates, 10 style recipes.
Stop your agent citing papers that don't exist. Verifies every reference against live PubMed & Crossref — flags fabricated, mismatched, and retracted citations.
by Nex AI
Add budget limits, approval workflows, and a policy-gated wallet layer to your autonomous agents.
Every RAG tutorial shows the same pipeline; almost none of it survives contact with your actual corpus
by Ryan lyell
A cognitive reasoning protocol and Markdown-based local memory system for high-stakes AI development and strategy.
Score and optimize any website for AI agent-readability using the Agent Ready REST API.
Scaffold a secure, spec-compliant MCP server from a description of the tools you want to expose. Sets up the official SDK (TypeScript or Python/FastMCP), defines tools/resources/prompts with strict JSON Schema, wires the right transport (stdio or Streamable HTTP), adds OAuth 2.1 for remote, and hardens against the MCP-specific footguns — prompt injection via tool output, token passthrough, over-broad scopes, command/path/SSRF injection, leaked secrets — before it ships. Returns a runnable skeleton plus a security checklist. Built by someone who's shipped production MCP servers.
Hardens AI prompts and agent workflows against logic errors, tool-misuse, and prompt injection.
by Shandra
Plans safe dependency upgrades and framework migrations for legacy applications with risk analysis, compatibility mapping, test planning, rollback strategy, and phased AI coding prompts.
Find the LLM integration code that will not survive a provider being pulled or going down. Flags single-provider lock-in with no alternative, calls with no failover branch, missing timeouts, retries with no limit or backoff, no degraded-mode default, and hardcoded endpoints with no alternate. This is about the model going away, not the model declining.
Inventory every LLM model and provider your code depends on, the AI bill of materials, and flag the dependency risk. It lists each provider, model, and where it's used, then flags hardcoded model ids, single-provider dependency with no alternative, the same model referenced by different ids, model ids with no config or env indirection, and providers pinned in your manifests. Recognizes OpenAI, Anthropic, Google Gemini, and more from an editable list.
Generate a spec-compliant llms.txt (and optional llms-full.txt) for your site or repo so AI agents and crawlers can navigate it. Curates the pages that matter, writes the exact llmstxt.org structure — single H1, blockquote summary, and link sections in the precise format agents parse — then validates the format and tells you where to put it. The honest version: a low-cost, machine-readable surface for the agentic web, not an overhyped SEO trick.
by Corey Jacobs
Run a buyer-readiness check before publishing an AI agent skill package.
by Roy Yuen
Secure encrypted secret management with automated health checks, expiration tracking, and rotation reminders.