Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Bounded planner-coder-reviewer workflows: status, verified run, and configured checks.
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
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"agenttrio": {
"command": "npx",
"args": [
"-y",
"@reneturcios/agenttrio",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add agenttrio -- npx -y @reneturcios/agenttrio mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"agenttrio": {
"command": "npx",
"args": [
"-y",
"@reneturcios/agenttrio",
"mcp"
]
}
}
}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": {
"agenttrio": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/agenttrio",
"mcp"
]
}
}
}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.
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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 6, 2026
The registry name was verified with the GitHub account CloudCorpRecords, 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 (0.1.0) reached the registry 4 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Apify MCP Server
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.
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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.
agenttrio runs bounded agent workflows made of three roles — a planner, a coder, and a separate read-only reviewer — against a local Ollama backend. It reports the workspace status, runs one task through the trio behind a host-enforced verification gate, and runs the workspace's configured checks. One binary serves a command-line interface and a stdio MCP server with exactly three tools.
Work is bounded by the operator config: model turns per role, coder → verification → reviewer cycles, total tool calls, and context size all have explicit budgets, and a run is only verified when the gate below passes — never on the model's say alone.
agenttrio reads an operator-reviewed TOML file. Passing --config explicitly approves loading that file; a workspace config.toml or .flow.toml is never auto-loaded. The only auto-loaded location is $XDG_CONFIG_HOME/flow/config.toml.
workspace_dir = "/absolute/path/to/workspace"
[ollama] base_url = "http://127.0.0.1:11434" model = "qwen2.5-coder:7b" timeout = 120
[models] planner = "qwen2.5-coder:7b" coder = "qwen2.5-coder:7b" reviewer = "qwen2.5-coder:7b"
[agent] max_iterations = 6 max_cycles = 2 max_tool_calls = 64 max_context_chars = 100000
[checks.test] cmd = ["npm", "test"] timeout = 60000 required = true kind = "test" filetypes = ["ts"]
Notes that matter:
timeout values are milliseconds; the Ollama timeout is seconds.--workspace overrides the config's workspace, and --model overrides every role's model.ollama.allow_remote = true.run and check require --trusted, which is what allows project edits and explicitly configured named checks.ollama serve and pull a tool-capable model (for example ollama pull qwen2.5-coder:7b) before expecting runs to work.npx @reneturcios/agenttrio status --config /path/to/operator.toml
Or run the container image:
docker run -i ghcr.io/cloudcorprecords/agenttrio
The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead; mount your config and workspace into the container if you use it that way.
agenttrio status --config operator.toml
agenttrio run "Fix the failing parser test" --config operator.toml --trusted agenttrio check --config operator.toml --trusted agenttrio check test --config operator.toml --trusted
agenttrio --version
Reports print as JSON. Exit codes follow the documented scheme: 0 on success, 1 for a runtime failure (including an unverifiable run configuration), and 2 for usage errors. Arguments are validated before any configuration is read, so a malformed invocation is always a usage error.
A run is reported verified: true only when all of these hold:
"approved": true).If the gate fails, the cycle repeats (coder → checks → reviewer) up to max_cycles, and the final report says verified: false with a note naming which condition failed.
One bin serves both faces. The mcp subcommand starts a stdio MCP server (newline-delimited JSON-RPC):
npx -y @reneturcios/agenttrio mcp --config /path/to/operator.toml --trusted
MCP client configuration:
{
"mcpServers": { "agenttrio": { "command": "npx", "args": ["-y", "@reneturcios/agenttrio", "mcp", "--config", "/path/to/operator.toml", "--trusted"] } } }
Replies carry the report as a JSON text block plus structuredContent; failures are returned as isError results. The server is deliberately sequential.
The tool list is intentionally only these three tools.
| Tool | Input | What it returns |
|---|---|---|
flow_status | {} | The status report: workspace, Ollama reachability and available models, per-role models, agent budgets, and configured checks. |
flow_run | {"task": "..."} | The run report: planner/coder output, check results, reviewer decision, cycles used, and the verified gate verdict. |
flow_check | {} or {"name": "configured-name"} | The check report: every result for the checks that ran and whether they all passed. Omit name to run all configured checks. |
npm install
npm run build # tsc -> dist/ npm test # node test runner over test/*.test.ts, no network (fake executor/fetch/runner only) npm run dev # run the CLI from source via tsx
MIT — see LICENSE.