Nicheloom

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CoChat MCP

Let your team review what your coding agent is building

Details

External ID
47002924
Source
HN
Company
—
Product
CoChat MCP
Website domain
github.com
Launched
Feb. 13, 2026
Cohort
—
Upvotes
5
Upvotes percentile
0.10512129380053908
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

I built an MCP server that connects coding agents (Claude Code, Cursor, OpenCode, Codex) to a collaborative workspace where your team and other AI models can review what the agent is planning.The problem: When Claude Code creates an implementation plan, it lives in your terminal session. Nobody else sees it until it becomes a PR. If you want GPT to check the architecture or a teammate to flag issues, you're copy-pasting between windows.This MCP server fixes that. When your agent creates a plan, it gets shared as a collaborative thread in CoChat. Engineers comment on it, other AI models review it, and you pull all the feedback back into your agent's context with one command. Decisions can be saved as project memories that persist across sessions and are searchable by anyone.What it does:Plans: Auto-shared as collaborative threads. Pull feedback back into your terminal. Cross-model review: Have GPT review your Claude plan, or vice versa. Project memories: Semantic memory that persists across sessions, models, and people. Ask: Query your project's knowledge base from the terminal. Auto-scoping: Detects your project from git remote. No config needed. Setup is one command per agent. Auto-share behavior is configurable (off/plan/all).MIT licensed, available on npm: npx @cochatai/mcp-cochatHappy to answer questions about the architecture or the MCP protocol integration.

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Agent / copilot
Audience
B2B
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
code review for ai agents
Manually corrected
False

Could you build this?

Yes It is an MCP (Model Context Protocol) server paired with a collaborative web dashboard, both of which follow standard API schemas and straightforward real-time web patterns.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 516 launches clear the similarity bar, closest 8 shown.

Attention rank: #500 of 517 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 101 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a agent / copilot tool for Agriculture yet.