# AgentStack (agentstack.tech) [Health: Active]

**Category:** 💻 Developer Tools  
**Repository:** https://github.com/agentstacktech/AgentStack  
**GitHub Stars:** 2  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/agentstack-agentstack-tech

## Description
Backend for AI agents: one batched tool over ~668 actions (hosting, storage, auth, payments).

## Claude Desktop Quick Installation
No confirmed install details yet, so no config is published. Follow the setup steps in the repository above.

## Documentation

## What AgentStack (agentstack.tech) MCP server does

The AgentStack (agentstack.tech) MCP server exposes AgentStack’s backend to an MCP client through one tool, `agentstack.execute`. Rather than requiring the model to browse a large action menu on each turn, the server keeps the plan and returns the next task through its Work Graph. The documented public catalog contains 714 MCP actions, while the server presents a single execution entry point.

The model can receive a ready action, a blocked state with the missing prerequisite, or an idle result. This makes the server relevant for agents that need to continue work across sessions, especially when tasks involve a shared project and changes to live data.

## How it works

The documented loop begins with a session and a project binding. The agent then calls `agents.work_next`, reads `packet.next_action`, claims or executes that action, and calls `work_next` again. The recipe for this flow is named `mcp_work_loop_v1`; the repository also identifies `agentstack_closed_loop_autonomy` as the associated prompt.

When an action changes live data, the project uses a safe-cycle sequence: connect, create or update a sandbox copy, review it, and promote it. Customers remain on the prior version while checks run. Publication may happen immediately or in stages according to the project’s own rule.

This design keeps the outcome and queue associated with the project. A later session can continue from the current head of the work queue rather than reconstructing the plan from the complete catalog.

## Tools and capabilities

The AgentStack (agentstack.tech) MCP server’s documented MCP surface is centered on `agentstack.execute`. Within the Work Graph flow, the material names these operations and response fields:

- `agents.work_next` obtains the next step for the bound project.
- `packet.next_action` carries the action the agent should take next.
- Claim and execute advance the selected work item.
- `discovery.search` can search the action registry when discovery is needed.

The repository describes the broader catalog as covering web-product, MCP, plugin, REST, RAG, sandbox, and example documentation. The supplied material also describes project work spanning a site and payments, but it does not provide a complete per-action inventory in this listing.

## Limitations and notes

The Work Graph targets are guidance, not measurements of current production traffic. The repository’s registry measurements were local, and its token estimates use an approximate bytes-divided-by-four method. The full catalog can be much larger than a single next-action packet, so integrations should avoid loading the entire catalog when a packet already supplies the next step.

The supplied documentation does not specify a local installation command, required environment variables, authentication values, or transport configuration. It also does not establish a license for the repository. Client-specific plugin repositories are named for Cursor, Claude Desktop or API, ChatGPT or OpenAI, and VS Code, but the excerpt does not provide detailed setup steps for those plugins.

The safe cycle is intended to keep live edits behind checks, but the excerpt does not define the project rules, validation checks, or promotion stages for a particular deployment. Those details must be obtained from the project and its linked Work Graph contract.

_Full upstream README: https://allmcps.com/mcp/agentstack-agentstack-tech/readme_