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.
npx agentmods add agents/asit-piri/agentic-knowledge-to-action/indexgit clone --depth 1 https://github.com/asit-piri/Agentic-Knowledge-To-ActionWrote 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.
[](https://agentmods.dev/agents/asit-piri/agentic-knowledge-to-action/index)<a href="https://agentmods.dev/agents/asit-piri/agentic-knowledge-to-action/index"><img src="https://agentmods.dev/badge/agents/asit-piri/agentic-knowledge-to-action/index.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00543 |
| Opus 5 | $0.00000 | $0.00271 |
| Sonnet 5 | $0.00000 | $0.00109 |
| Haiku 4.5 | $0.00000 | $0.00054 |
Grade A, and why
index 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 5d 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.
This is a copy
84% identical to index — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Integrations
This section provides guidance on integrating various AI agent frameworks with the Model Context Protocol (MCP) Gateway. MCP enables agents to dynamically discover and utilize tools across multiple servers, enhancing their capabilities and flexibility.
🧠 Supported Agent Frameworks
Using ContextForge (Agent frameworks as MCP clients)
- LangChain: Utilize MCP tools within LangChain agents using the
langchain-mcp-adapterspackage. - LangGraph: Integrate MCP tools into LangGraph agents for advanced workflow orchestration.
- CrewAI: Connect CrewAI agents to MCP servers using the
crewai-toolslibrary. - Bee Agent Framework: Leverage MCP tools within the Bee Agent Framework for scalable agent deployments.
- AutoGen: Integrate MCP tools with AutoGen agents using the
autogen-ext-mcppackage. - LlamaIndex: Incorporate MCP tools into LlamaIndex workflows for enhanced data retrieval and question answering.
- OpenAI Agents SDK: Utilize MCP tools within OpenAI's Agents SDK for building AI agents with standardized tool access.
- Semantic Kernel: Connect Semantic Kernel agents to MCP servers for enriched context and tool integration.
A2A (Agent-to-Agent) Integration (External agents in ContextForge)
- A2A Integration: Complete guide to registering external AI agents in ContextForge
- External AI Agents: Register external AI agents (OpenAI, Anthropic, custom) as A2A agents in the gateway
- Tool Exposure: A2A agents are automatically exposed as MCP tools for other agents to discover and use
- Protocol Support: Supports JSONRPC, custom protocols, and multiple authentication methods
- Admin Management: Full admin UI for registering, testing, and managing external agents
- Virtual Server Integration: Associate A2A agents with virtual servers for organized tool catalogs
🔍 Overview
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.
- 5d ago First seen · 46 lines · 0 tokens per session scan A 6da5357e5874
index is an agent published in the GitHub repository asit-piri/Agentic-Knowledge-To-Action (0 stars, last pushed 6mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 543 tokens. A static security scan graded it A with 0 findings. It is 84% identical to index, differing in 2 lines, and is treated as a copy.
Other agents, from other repositories
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code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.