Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Manifold

by nonchan7720version 1.25.1i★ –iRuns on your computer
Registry nameio.github.nonchan7720/manifold

Install

Overview

Description from the maker (original English)

MCP gateway aggregating MCP servers and OpenAPI/Swagger REST APIs behind one MCP endpoint

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: Streamable HTTP
  • Category: Developer tools
  • You need to fill in: ENCRYPT_KEY, SERVER_NAME

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: ENCRYPT_KEY, SERVER_NAME

Values marked secret are keys to your account. Never share them or paste them into a chat.

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": {
    "manifold": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "ENCRYPT_KEY",
        "-e",
        "SERVER_NAME",
        "ghcr.io/nonchan7720/manifold:v1.25.1"
      ],
      "env": {
        "ENCRYPT_KEY": "your-value",
        "SERVER_NAME": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add manifold --env ENCRYPT_KEY=your-value --env SERVER_NAME=your-value -- docker run -i --rm -e ENCRYPT_KEY -e SERVER_NAME ghcr.io/nonchan7720/manifold:v1.25.1

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "manifold": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "ENCRYPT_KEY",
        "-e",
        "SERVER_NAME",
        "ghcr.io/nonchan7720/manifold:v1.25.1"
      ],
      "env": {
        "ENCRYPT_KEY": "your-value",
        "SERVER_NAME": "your-value"
      }
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "manifold": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "ENCRYPT_KEY",
        "-e",
        "SERVER_NAME",
        "ghcr.io/nonchan7720/manifold:v1.25.1"
      ],
      "env": {
        "ENCRYPT_KEY": "your-value",
        "SERVER_NAME": "your-value"
      }
    }
  }
}

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.

Values you fill in

  • ENCRYPT_KEY secret required env
    Base64-encoded 32-byte AES-256 key used to encrypt stored tokens (generate with: openssl rand -base64 32)
  • SERVER_NAME required env
    Name of a backend server defined under mcpServers in config.yaml; forms the MCP endpoint path /mcp/{SERVER_NAME} (not read by the container itself)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account nonchan7720, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 4900 servers in this category
  • Published to the registry more recently than 90% of the other 4900 servers in this category
  • Basic checks equal to or better than 100% of the other 4900 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Manifold safe?

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.

What keys or codes does it need?

You need to fill in: ENCRYPT_KEY, SERVER_NAME

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.25.1) reached the registry 3 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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

GitHub

by github

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

Computer or cloud★ 34,245MITUpdated 4 days ago
Install

Desktop Commander

by wonderwhy-er

MCP server for terminal commands, file operations, and process management

Runs on your computer★ 10,225MITUpdated 16 days ago
Install

Cloudflare MCP

by cloudflare

Cloudflare MCP servers

Runs in the cloud★ 4,446Apache-2.0Updated 14 months ago
Install

README from the maker

Open the README

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.

Manifold

One interface. Many connections. Manifold.

English | 日本語

Manifold is a gateway that acts as an MCP server while connecting to multiple external MCP servers and OpenAPI / Swagger-compliant REST APIs on the backend.

Why "Manifold"?

The name Manifold comes from an engine's intake manifold.

An intake manifold is the component that distributes air and fuel evenly and efficiently from a single inlet to multiple cylinders. We named this project Manifold because its structure is similar.

Engine manifoldThis project
Single inletRequests from MCP clients
Distribution / routingProtocol conversion / routing
To multiple cylindersTo multiple external MCP / REST APIs

Architecture

flowchart TD

client["MCP Client"] --> manifold["Manifold (this server)"] manifold --> mcp["External MCP Servers"] manifold --> rest["OpenAPI / Swagger REST API Servers"] manifold --> a2a["A2A Agents"]

Features

  • OpenAPI / Swagger → MCP conversion: Automatically generates MCP tools from OpenAPI 3.x / Swagger 2.x specifications
  • Static tool catalog: Inspect the MCP tools an OpenAPI spec would generate before starting the gateway (manifold openapi tools), and start from a committed, diffable generated file instead of fetching the spec at boot (manifold openapi generate, mcpServers. .tools.file)
  • Breaking-change detection: Classify upstream spec changes as breaking or not with oasdiff, mapped to the affected MCP tools (manifold openapi diff, manifold openapi generate --check)
  • MCP backend aggregation: Transparent reverse proxy to external MCP servers, relaying their tools and prompts
  • Tool filtering and renaming: Expose only the tools you need, under the names and descriptions you choose (mcpServers. .tools.include / exclude / overrides)
  • Audit log: Write one JSON line per tool call (audit)
  • A2A agents as MCP servers: Expose an A2A (Agent2Agent) agent's Agent Card skills as MCP tools, either served on their own (agents) or attached to a service (mcpServers. .agents, skills exposed as __ tools next to the service's own tools), with the caller's session id carried as the A2A contextId and the response context returned in _meta.a2a
  • Built-in OAuth 2.1 server: Authorization server with PKCE (S256) support. Downstream clients register through DCR (RFC 7591) or a client ID metadata document (CIMD), and can be mapped one-to-one onto upstream OAuth clients
  • Pluggable backend authentication: Choose one of static header (authValue) / OAuth 2.0 (oauth2) / API key Token Exchange (tokenExchange) / Google service account (googleServiceAccount)
  • MCP Apps: Passes MCP Apps (io.modelcontextprotocol/ui) UIs of MCP backends through to hosts that support them — _meta.ui on tools, and the ui:// resources via resources/list / resources/read — and strips them for hosts that don't (mcpServers. .apps)
  • Resource links: Stores binary content from tool responses (including format: binary fields inside JSON responses) in S3 and returns download URLs (resource links)
  • Lazy connection (stdio) / stateless connection (http): stdio backends connect on first request (no backend dependency at gateway startup); http backends open a fresh connection per request and never share a session across callers
  • Selectable storage: Session / token management in memory (default), Redis or SQLite
  • OpenTelemetry support: OTLP export of traces, metrics, and logs (metrics also support Prometheus-style pull)

Requirements

  • Nothing else for the prebuilt binary or Docker image. Go 1.26+ to build from source
  • Optional: Redis or SQLite, to keep sessions and OAuth tokens across restarts or share them between replicas. Without either, Manifold keeps them in memory

Installation

Download binary

Download the latest binary from Releases.

Build from source
git clone https://github.com/nonchan7720/manifold.git

cd manifold go build -o manifold .

Docker
docker pull ghcr.io/nonchan7720/manifold:latest

Usage

Start the gateway
# Run the binary

manifold gateway

Specify a config file explicitly (-c / --config, config name without extension)

manifold gateway -c config

Run from source

go run main.go gateway

Docker (working directory is /home/nonroot)

docker run -p 9999:9999 \ -v $(pwd)/config.yaml:/home/nonroot/config.yaml \ ghcr.io/nonchan7720/manifold:latest

Docker Compose (development)

Starts a development environment including Redis.

docker compose up -d

Ready-to-run configuration examples are available in the examples/ directory.

Inspect and generate MCP tools

For OpenAPI-mode servers (spec and/or tools.file configured), manifold openapi shows what the gateway would register, and can write it to a file the gateway starts from — without ever fetching the spec at boot.

# Print the tools every OpenAPI-mode server would register (no gateway started)

manifold openapi tools -c config

One server, with the full inputSchema

manifold openapi tools -c config --server petstore --json

Write the generated tools file for every server that has tools.file configured

(errors for a server that has no spec configured)

manifold openapi generate -c config

CI: fail if the committed file doesn't match the live spec, without writing anything

manifold openapi generate -c config --check

Show breaking changes between the committed file and the live spec (oasdiff)

manifold openapi diff -c config

openapi tools output:

SERVER    TOOL          OPERATION          DESCRIPTION

petstore addpet POST /pet Add a new pet to the store. petstore getpetbyid GET /pet/{petId} Find pet by ID.

The generated file (tools.file) is YAML, with a diffable tools section followed by the resolved spec:

version: 1

generatedBy: manifold 1.12.0 source: spec: https://petstore3.swagger.io/api/v3/openapi.json sha256: "..." fetchedAt: "2026-09-04T00:00:00Z" format: openapi3 tools:

  • name: getpetbyid operation: GET /pet/{petId} description: Find pet by ID. binaryResponse: false inputSchema: { ... }

spec: { ... } # openapi3 document, external $refs internalized

Binary fields and responses

A format: binary property in a multipart/form-data, application/x-www-form-urlencoded or application/json request body (for Swagger 2, type: file form parameters and format: binary fields inside an in: body schema, including nested objects, arrays, $ref and allOf) is not exposed as a plain string. It becomes a oneOf that accepts either a string (base64 content or a URL to fetch the file from) or an object naming the source explicitly (url / base64 / text / content, plus optional filename and contentType), and carries _meta.manifold.file: true so clients can recognize it as a file input. An operation whose success response is binary (e.g. image/png, application/octet-stream) is marked binaryResponse: true; at runtime such responses are handled as binary content and, when storage is configured, returned as resource links (see storage). Only a successful (2xx) response whose actual Content-Type is not textual is treated as binary: error responses, 3xx responses and text/JSON/XML/YAML bodies (including +json / +xml types) are returned as-is even for a binaryResponse: true tool. From a spec with one upload and one download operation:

tools:
  • name: uploadfile operation: POST /files description: Upload a file binaryResponse: false inputSchema: properties: file: _meta: manifold: file: true fileInputHint: 'Provide the file content as a base64-encoded string, or as a URL (e.g. a presigned URL) to download the file from. For explicit control, an object may be passed instead with one of these keys: {url:"..."} ...' description: File to upload oneOf:
  • description: Base64-encoded file content, or a URL (e.g. a presigned URL) to download the file from. type: string
  • description: Explicit file source; provide exactly one of url/base64/text/content. properties: base64: { type: string, description: Base64-encoded file content. } url: { type: string, description: URL to download the file content from. } text: { type: string, description: Raw (non-base64-encoded) text file content. } content: { type: string, description: Legacy auto-detected base64 or URL content. } filename: { type: string, description: Filename to use for the upload. } contentType: { type: string, description: MIME content type to use for the upload. } type: object label: _meta: {} description: "" type: string required:
  • file type: object
  • name: downloadfile operation: GET /files/{fileId}/content description: Download a file binaryResponse: true inputSchema: properties: fileId: description: "" type: string required:
  • fileId type: object

In a JSON request body, a binary field's value is resolved the same way (base64, URL or explicit object) and sent to the upstream API as base64. Conversely, a format: binary field inside a 2xx JSON response (Swagger 2: format: binary or type: file; nested objects and arrays included, OpenAPI 3.1 contentMediaType used as the content type) is uploaded to storage when it is configured: the base64 value in the JSON is replaced with its download URL, and a resource link is added to the result for each uploaded field. Without storage, or for null / non-base64 values, the JSON is returned unchanged.

Recommended workflow:

  1. Add tools.file to the server's config (see mcpServers. .tools) and run manifold openapi generate -c config.
  2. Commit the generated file. Its tools section makes upstream spec changes reviewable as a normal PR diff.
  3. Start the gateway (manifold gateway -c config) — it reads the tools from the file, with no network access to spec at startup.
  4. After the upstream spec changes, re-run manifold openapi generate -c config and commit the update. A stale file (spec changed but the file wasn't regenerated) fails gateway startup with an error telling you to regenerate.
  5. Add manifold openapi generate -c config --check as a CI step, so a PR that changes the upstream spec without regenerating the file fails before merge.

CI: --check only checks servers with tools.file configured — a server without one is skipped with a stderr note, and --server restricts the check to a single server. For each, it rebuilds the catalog from the live spec and compares it against the committed file: source.sha256 (the upstream spec's raw bytes), the tools section, and the embedded spec section (the internalized document the gateway actually runs from) — generatedBy a

Only the beginning is shown; read the rest in the repo

Ask PopNx