Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Runtime governance enforcement for AI agents. Zero token overhead.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"aegis": {
"command": "npx",
"args": [
"-y",
"aegis-mcp-server"
]
}
}
}Run this in your terminal
claude mcp add aegis -- npx -y aegis-mcp-serverPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"aegis": {
"command": "npx",
"args": [
"-y",
"aegis-mcp-server"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"aegis": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"aegis-mcp-server"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account cleburn, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.15) reached the registry 8 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, ScienceShot science reference
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Sourced, citable answers in radiation and particle physics, photonics, electronics and quantum.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
MCP enforcement layer for the [Aegis](https://github.com/cleburn/aegis-spec) agent governance specification.
Policy at the root. Enforcement at runtime. Accountability on every action.
aegis-mcp-server is an MCP server that validates every agent action against your .agentpolicy/ files before it happens. Path permissions, content scanning, role boundaries, quality gates — all enforced at runtime with zero token overhead to the agent.
The agent never loads your governance files. The MCP server reads them into its own process memory and validates silently. The agent calls governed tools and gets back either a success or a blocked response with the specific reason.
# Install globally
npm install -g aegis-mcp-server
If you generated your policy with aegis-cli, the .mcp.json connection config is already in your project root. Just install the MCP and open your agent — it connects automatically.
When starting a new agent session in a governed project, use this as your first prompt:
Call aegis_policy_summary now. This is your governance contract — it defines your
role, your boundaries, and which tools to use. Do not take any action until you have called this tool and received confirmation from the user to proceed.
For initial builds, the Aegis CLI generates a custom handoff prompt tailored to your project — use that instead.
The MCP starts without a pre-assigned role. When the agent calls aegis_policy_summary, it receives the list of available roles — including the built-in construction role and all specialist roles from .agentpolicy/roles/. The agent presents them to the user, the user picks, and the agent calls aegis_select_role to lock in. All enforcement uses the selected role for the rest of the session.
This is the default behavior — no configuration needed beyond the .mcp.json that aegis init creates automatically.
The construction role is always available for initial builds and major restructuring. When selected:
.agentpolicy/ files serve as the blueprint — the agent reads constitution, governance, and role files to understand the project's architecture, conventions, and quality standardsstate/overrides.jsonl with a timestamp and human_confirmed: trueaegis_complete_task to run quality gates and close construction mode — the closing timestamp is logged alongside the opening entryConstruction mode is not a bypass — the agent still follows the governance files as its blueprint. It's a speed optimization for greenfield builds where enforcing write restrictions on every file would be counterproductive.
If you know which role to assign at startup:
{
"mcpServers": { "aegis": { "command": "aegis-mcp", "args": ["--project", ".", "--role", "backend"] } } }
The MCP locks to that role immediately. aegis_policy_summary returns the role's boundaries directly, skipping role selection.
| Tool | What it does | Token cost |
|---|---|---|
aegis_policy_summary | Role boundaries and governance summary (or available roles in universal mode) | ~200 tokens |
aegis_select_role | Select a role (including construction) in universal mode | Tiny |
aegis_check_permissions | Pre-check if an operation is allowed | Tiny |
aegis_write_file | Governed write with path + content validation | Same as a normal write |
aegis_read_file | Governed read with path validation | Same as a normal read |
aegis_delete_file | Governed delete with path validation | Tiny |
aegis_execute | Governed command execution | Command output only |
aegis_complete_task | Run quality gates and close construction mode if active | Gate results only |
aegis_request_override | Execute a blocked action after human confirmation | Tiny |
Traditional approach: load governance files into the agent's context window. Token cost scales with policy complexity.
Aegis MCP approach: the server loads policy into its own process memory. The agent calls tools and gets structured results. A project with 200 lines of governance has the same token cost as one with 20 lines. The complexity is absorbed by the server, not the agent.
writable, read_only, forbidden path listspre_commit flags mapped to build_commands and executedoverrides.jsonlWhen an action is blocked and the governance override behavior is warn_confirm_and_log:
override_token and the specific policy violatedaegis_request_override with the token and the user's rationalehuman_confirmed: trueImmutable policies (e.g., HIPAA compliance, ITAR data sovereignty, audit completeness) return override_available: false and cannot be overridden. The user must modify the governance through aegis init.
The Aegis MCP does not override the agent's native directives. It introduces itself through tool descriptions, explains why governance is active, and asks the agent to seek user permission to route write operations through Aegis tools. The user's authority is the enforcement mechanism.
Native tools for reading, searching, and exploring the codebase work fine without governance gating. Only write, delete, and execute operations benefit from routing through Aegis.
Agent ──→ aegis-mcp-server ──→ File System
│ ├── Loads .agentpolicy/ into process memory (once) ├── Watches for policy changes (auto-reload) ├── Validates every tool call against policy ├── Returns success or blocked with override option └── Logs all enforcement decisions to overrides.jsonl
Three artifacts, one governance framework:
MIT