SnitchFeed × Major: build agents that act on intents while the thread is live

Act on every buyer intent signal automatically

SnitchFeed surfaces the people who need you right now: buyers asking for recommendations, complaining about a competitor, or describing the exact problem your product solves.

The hard part has never been finding them. It is acting on all of them.

A signal that arrives in Slack and stays in Slack is a to-do item with better timing. As covered in social listening vs social monitoring, if the output is a reply, someone still has to write it.

That changes today. 

We're partnering with Major.build, an enterprise platform for building, deploying and governing AI agents and applications.

What the integration does

Major connects to anything with an API or an MCP. Authenticate your SnitchFeed workspace once, and you can build agents and applications that read your signals alongside the rest of your stack.

The difference from a standard automation tool is in how Major builds. It separates a described workflow into two kinds of work. The deterministic parts become a real application, with a managed database and real code behind it rather than a dashboard layered over your existing tools. The parts requiring judgment stay with an agent, which calls that application to get work done.

The result is that most of each run travels deterministic paths instead of being re-reasoned inside a context window. Concurrent runs get cheaper and more reliable rather than more expensive.

That mirrors the economics of social listening itself. Detecting a buyer is inexpensive. Responding to every buyer is where the cost accumulates. Previous coverage of social listening APIs and MCP servers made the case that agents should manage monitoring rather than only read it. This integration is the step after that, where the agent acts on what it finds.

What you can build

A content engine driven by real demand. An agent reads SnitchFeed for topics your market is actively discussing, drafts a post, and schedules it through your existing scheduling tool. The same signal set that surfaces high-intent leads on LinkedIn also tells you what those people are asking about.

Replies at the speed the thread moves. Buyer intent signals on Reddit decay fast, and the useful reply window is short. An agent can draft the response, route it for approval, and post it while the conversation is still live.

SEO keyword research from actual questions. Rather than starting with a keyword tool and inferring demand, start with the questions being asked and work backwards.

A worked example

Ritvij Gautam, head of growth at Major, built a LinkedIn content engine on the connector. The full build is in the video below.

The input was a single paragraph of plain English: SnitchFeed and Taplio both connected, a content calendar app plus an agent that finds trending topics in SnitchFeed, writes a post, schedules it in a morning window, and displays past posts with engagement stats.

Major then queried the specification before building it. The requested window was 9 to 11am with two posts seven hours apart, which is impossible, so it asked how the cadence should work. It also asked whether to cache Taplio data in its own Postgres or read live on every run.

About twenty minutes later there was a working content calendar application with a real backend, plus an agent with access to SnitchFeed, Taplio and the company blog. It had added a guardrail that was never requested, skipping days with content already scheduled and rolling posts to the next open slot.

Approval and access control

An agent acting on public social signals needs limits, and Major provides them on its side.

Publishing can be gated behind approval. In the build above, the agent sends a Slack message and waits for a green light before anything goes out.

Major also works with what already exists in a workspace rather than around it. During the build it identified an existing LinkedIn content agent and extended it instead of creating a duplicate, and it flagged an application it did not have permission to modify rather than silently skipping it. Managed credentials, per-team access control, full action logging, SOC 2 Type I and self-hosting for data residency are all handled by Major.

Getting started

Major is offering existing SnitchFeed users $100 in free build credits to build their first agents or applications. 

On the SnitchFeed side, the MCP server is included on every plan and takes a single OAuth to connect in Claude, ChatGPT or Cursor. The full tool reference covers everything the server exposes.