Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Route MCP capabilities through deterministic identity, policy, budget, and deadline constraints.
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.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"gaugemesh": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/aliengineering-byte/gaugemesh@sha256:69f3ccb7c2fdcd9b6897c99eba22d18be1384957bb2dbdf760f8273ee2e43189",
"mcp-stdio"
]
}
}
}Run this in your terminal
claude mcp add gaugemesh -- docker run -i --rm ghcr.io/aliengineering-byte/gaugemesh@sha256:69f3ccb7c2fdcd9b6897c99eba22d18be1384957bb2dbdf760f8273ee2e43189 mcp-stdioPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"gaugemesh": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/aliengineering-byte/gaugemesh@sha256:69f3ccb7c2fdcd9b6897c99eba22d18be1384957bb2dbdf760f8273ee2e43189",
"mcp-stdio"
]
}
}
}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": {
"gaugemesh": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/aliengineering-byte/gaugemesh@sha256:69f3ccb7c2fdcd9b6897c99eba22d18be1384957bb2dbdf760f8273ee2e43189",
"mcp-stdio"
]
}
}
}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.
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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 aliengineering-byte, 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 (0.4.1) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, SSTracker free youth training
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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One endpoint for MCP capabilities and model routes—without losing identity, authority, budgets, deadlines, side-effect semantics, or causal evidence between protocols.
GaugeMesh is a local-first Rust developer preview. It is deliberately narrower than a general AI gateway: every adapter must preserve declared invariants or reject the operation before a side effect. Route selection is fixed-point, deterministic, and explainable. The base deployment is one binary with memory or SQLite; it needs no hosted control plane, Redis, PostgreSQL, Docker, or Kubernetes.
Install without Rust from the checksummed, attested GitHub Release or run the multi-architecture GHCR image. Crates.io is not a GaugeMesh distribution channel. The real stdio MCP server is gaugemesh mcp-stdio; its Official MCP Registry metadata is checked in as server.json.
The source tree also provides opt-in bounded durable Runs: caller-authored plans over the existing Tasks, verified file outcomes, explicit resume/cancel, and offline evidence verification. See that contract for the local Unix boundary and the external installed-binary qualification commands.
Two explicit first-use paths are available from release source:
From a release archive:
gaugemesh demo
From source with Rust 1.88 or newer:
cargo run --locked --release -- demo
No account, credential, provider, network target, database, container, or existing MCP server is used. The command writes no file to the caller directory.
Actual output from the 0.1.0 release binary:
GaugeMesh demo
[ok] 2 MCP sources connected [ok] 1 model route connected [ok] colliding tool names isolated by capability identity: true [ok] 2 capabilities leased [ok] route selected under cost, deadline, and policy bounds [ok] deterministic failure reproduced [ok] recovery bounded to one attempt [ok] duplicate effects: 0 [ok] invariants preserved or strengthened: 23/23 [ok] cleanup complete: no owned child or listener remains
Route: local-model -> docs-a__search Decision: sha256:169a6315aa69eb7fa3e3b5aae70ede14d4c9ec71c0281d217fd84201414567f1 Evidence: sha256:9a9cdc8b673bab79ae96cf5aba5b7895d6e6e5f425407d1bd64da8701a1314e6
search name without sharing an authorization identity.The demo is deterministic fixture evidence, not a production-duration soak or security certification.
Inspect the route planner and its versioned decision contract independently. The final command uses a built-in fixture in which every candidate violates a hard constraint, so the output is a digest-bound denied decision rather than an unsafe fallback:
gaugemesh route explain
gaugemesh route explain --decision-contract gaugemesh route explain --deny-all gaugemesh route schema gaugemesh route validate decision.json
MCP clients --------------------+ /mcp
| OpenAI-compatible clients ------+--> GaugeMesh --> invariant + policy boundary | | before execution MCP servers needing models -----+ /v1/* +--> MCP stdio / Streamable HTTP +--> OpenAI-compatible providers +--> official/private registries
ResiliReplay ---------------------- verification only; never a production hop
GaugeMesh is an MCP server northbound and an MCP client southbound. It is an OpenAI-compatible server northbound and a client of configured compatible model providers southbound. Registry records are discovery metadata, not execution authority.
Create a strict loopback configuration:
gaugemesh init
Review and add a local stdio server. --command must resolve to an absolute executable and is launched with an argument array, never through a shell:
gaugemesh add mcp docs \
--command "$(command -v gaugemesh)" \ --arg mcp-stdio \ --protocol-revision 2025-11-25
add performs live discovery and writes the source only after tools, resources, templates, prompts, server identity, and revision are readable. serve loads reviewed sources into a bounded runtime, pins the capability snapshot, and rejects schema drift. Tools, resources, and prompts keep source-bound opaque identities even when readable aliases collide. Streamable HTTP sources use the same command with a reviewed --url; Registry search/inspect/approve is a separate trust path and never installs or executes a discovered package.
The provider must expose a compatible /v1/models endpoint. To exercise the complete no-key setup, keep gaugemesh serve running in one terminal and add its built-in local model route from another:
gaugemesh serve
gaugemesh add model local-provider \
--base-url http://127.0.0.1:8090/v1/ \ --provider-model-id local \ --context-limit 8192 \ --max-output-tokens 1024 \ --cost-table-version local-2026-08-30
For a credentialed provider, pass the environment-variable name, not its value:
gaugemesh add model hosted \
--base-url https://provider.example.test/v1/ \ --provider-model-id reviewed-model \ --credential-env PROVIDER_API_KEY \ --cost-table-version contract-2026-08
Configured routes are checked against capability, context, deadline, token, money, retry, data, and side-effect limits before selection. Cost tables are version-bound; estimates are not presented as provider billing facts.
Start the data and separately bound health listeners:
gaugemesh doctor
gaugemesh list gaugemesh serve gaugemesh connect generic-mcp
Loopback defaults are http://127.0.0.1:8090/mcp for Streamable HTTP, http://127.0.0.1:8090/v1 for the model API, and http://127.0.0.1:8092/healthz for health. The official MCP conformance client connects to /mcp separately for both supported revisions. GaugeMesh also has real RMCP integration tests as an upstream client over stdio and Streamable HTTP. Product-specific client installers are not emitted without installation evidence.
Point a client that supports a custom base URL at GaugeMesh:
gaugemesh connect openai-compatible
curl http://127.0.0.1:8090/v1/chat/completions \ -H 'content-type: application/json' \ -d '{"model":"local","messages":[{"role":"user","content":"hello"}]}'
The release gate also executes openai-python==3.6.0 against that base URL for model listing, chat completions, and Responses. The implemented surface is GET /models, POST /chat/completions, and POST /responses, with bounded JSON and SSE behavior. Unknown request fields are rejected. This is a verified subset, not complete OpenAI API compatibility.
Tool execution is off unless a request explicitly selects a GaugeMesh mode and bound:
x-gaugemesh-tool-mode: lease
x-gaugemesh-max-tool-rounds: 1 x-gaugemesh-deadline-ms: 3000
These extension headers are not OpenAI fields. An MCP server can call /v1/* directly for model access; deprecated MCP sampling is not silently converted. Unsupported sampling and elicitation paths return stable errors or enter an explicit approval backend.
Run gaugemesh route explain for the original 0.1.0 bare plan containing accepted and rejected candidates, integer score terms, the stable tie breaker, and policy/metric snapshot digests. Existing machine consumers retain that shape. Opt into the versioned selected wrapper with --decision-contract. gaugemesh route explain --deny-all returns the new contract with status: "denied", stable GM_ROUTE_NO_ELIGIBLE_CANDIDATE, every constraint rejection, and the snapshot digests. Route IDs must be unique, denied candidates must carry nonblank reasons, and candidate/reason ordering is canonical. Both selected and denied contracts include decision_digest, a SHA-256 digest over the canonical unsigned decision fields other than the digest itself.
The checked-in route-decision JSON Schema documents the wire contract. Save a decision and run gaugemesh route validate to check its schema, digest, and derivable selection/denial invariants entirely offline. The digest is unsigned and recomputable integrity, not authentication against a party able to rewrite the whole decision. Decisions contain route IDs and constraint reasons; validation does not upload them, and they should be sanitized before sharing. The analogy boundary is documented in the physics model.
0.1.0 remote listener authenticates OIDC bearer tokens rather than exposing an API-key administration service.kill_on_drop, startup/framing limits, restart budgets, and a security-partitioned process key. Unknown servers are non-shareable.See SECURITY.md, THREAT_MODEL.md, and the adversarial evidence. The bounded durable MCP Tasks route documents its separate failure and trust boundaries. GaugeMesh does not claim exactly-once execution, production readiness, universal client/provider support, official MCP status, MCP certification, or security certification.
| Surface | Eviden
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