The prevailing wisdom in the agentic AI space is that progress lies in building standardized servers and directories for tool discovery (like MCP). After extensive development, we believe this approach, while well-intentioned, is a cumbersome and inefficient distraction. It fundamentally misunderstands the bottleneck of today's LLMs.
The problem isn't a lack of tools; it's the painful and manual labor to setup, configure and connect to them.
Pre-defined MCP tool lists/directories, are inferior for several first-principle reasons:
- Reinventing the Auth Wheel: The key improvement of MCP's was supposed to be you get to package a bunch of tools together and solve the auth issue at this server level. But the user still has to configure and authenticate to the server using API key or OAuth.
- Massive Context Pollution: Every tool you add eats into the context window and risks context drift.
- Brittleness and Maintenance: If an API on the server-side changes, the MCP server must be updated.
- The Awkward Discovery Dance: It's a clunky user experience to discover the right server and then manually configure, defeating the purpose of seamless automation.
We propose a more elegant solution: Stop feeding agents tool lists. Let them build the tool they need, on the fly.
Our insight was simple: The browser is the authentication layer. Your logins, cookies, and active sessions are already there. An AI Web Agent can just reuse these credentials, find your API key and construct a tool to use. If you have an API key on your screen, you have an integration. It's that simple.
Our AI Web agent can now look at a webpage, find an API key, and be prompted to generate the necessary Javascript tool to call the desired endpoint at the moment it's needed.
This approach:
- The user now just has to prompt an agent as opposed to the prior manual steps of finding a MCP Server, setting up, and authenticating to it.
- Keeps the context window clean and focused on the task at hand.
- No maintenance/debugging overhead. An API update? Just point the agent to the new docs and it will configure an updated version.
We wrote a blog post that goes deeper into this architectural take and shows a full demo of our agent creating a HubSpot tool from API key on page and using it in the same multi-step workflow of then loading contacts from LinkedIn with the new tool.
We think this is a more scalable and efficient path forward for agentic AI.
The prevailing wisdom in the agentic AI space is that progress lies in building standardized servers and directories for tool discovery (like MCP). After extensive development, we believe this approach, while well-intentioned, is a cumbersome and inefficient distraction. It fundamentally misunderstands the bottleneck of today's LLMs.
The problem isn't a lack of tools; it's the painful and manual labor to setup, configure and connect to them.
Pre-defined MCP tool lists/directories, are inferior for several first-principle reasons:
- Reinventing the Auth Wheel: The key improvement of MCP's was supposed to be you get to package a bunch of tools together and solve the auth issue at this server level. But the user still has to configure and authenticate to the server using API key or OAuth.
- Massive Context Pollution: Every tool you add eats into the context window and risks context drift.
- Brittleness and Maintenance: If an API on the server-side changes, the MCP server must be updated.
- The Awkward Discovery Dance: It's a clunky user experience to discover the right server and then manually configure, defeating the purpose of seamless automation.
We propose a more elegant solution: Stop feeding agents tool lists. Let them build the tool they need, on the fly.
Our insight was simple: The browser is the authentication layer. Your logins, cookies, and active sessions are already there. An AI Web Agent can just reuse these credentials, find your API key and construct a tool to use. If you have an API key on your screen, you have an integration. It's that simple.
Our AI Web agent can now look at a webpage, find an API key, and be prompted to generate the necessary Javascript tool to call the desired endpoint at the moment it's needed. This approach:
- The user now just has to prompt an agent as opposed to the prior manual steps of finding a MCP Server, setting up, and authenticating to it.
- Keeps the context window clean and focused on the task at hand.
- No maintenance/debugging overhead. An API update? Just point the agent to the new docs and it will configure an updated version.
We wrote a blog post that goes deeper into this architectural take and shows a full demo of our agent creating a HubSpot tool from API key on page and using it in the same multi-step workflow of then loading contacts from LinkedIn with the new tool.
We think this is a more scalable and efficient path forward for agentic AI.
The full write up is here: https://www.rtrvr.ai/blog/on-the-fly-toolgen