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

legacy2mcp

by bvenkataversion 0.5.1i★ –iRuns on your computer
Registry nameio.github.bvenkata/legacy2mcp

Install

Overview

Description from the maker (original English)

Turn a legacy SOAP/WSDL, database, or REST API into a safe, typed, audit-logged MCP server

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: stdio
  • Category: Databases & datasets

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).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

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": {
    "legacy2mcp": {
      "command": "uvx",
      "args": [
        "legacy2mcp",
        "run",
        "--config"
      ]
    }
  }
}

Run this in your terminal

claude mcp add legacy2mcp -- uvx legacy2mcp run --config

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

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

{
  "mcpServers": {
    "legacy2mcp": {
      "command": "uvx",
      "args": [
        "legacy2mcp",
        "run",
        "--config"
      ]
    }
  }
}

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 needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "legacy2mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "legacy2mcp",
        "run",
        "--config"
      ]
    }
  }
}

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.

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 bvenkata, 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 Databases & datasetsi

  • More stars than 0% of the other 1139 servers in this category
  • Published to the registry more recently than 72% of the other 1139 servers in this category
  • Basic checks equal to or better than 100% of the other 1139 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 legacy2mcp 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?

The registry does not list a required key, though some servers ask you to sign in on first use.

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 (0.5.1) reached the registry 16 days ago.

Which apps can use it?

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

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

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

Supabase

by supabase

Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.

Computer or cloud★ 2,993Apache-2.0Updated yesterday
Install

MongoDB MCP Server

by mongodb-js

MongoDB Model Context Protocol Server

Runs on your computer★ 1,157Apache-2.0Updated 3 days 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.

legacy2mcp

Convert anything to MCP in 60 seconds. Read-only by default, with every call audit-logged.


Quick start

No API key, no cloning — pick whichever matches what you actually have, against live public demo targets:

pip install legacy2mcp

REST API -- tries OpenAPI/Swagger discovery

legacy2mcp init --rest-url "https://petstore3.swagger.io/api/v3"

WSDL / SOAP service -- zeep introspects it live, no scan needed

legacy2mcp init --wsdl-url "http://www.dneonline.com/calculator.asmx?WSDL"

A website with no API docs at all -- crawls it for forms/content

legacy2mcp init --webpage-url "https://legacy2mcp.com/"

Run any one of those from a real terminal and that's the whole thing: it writes config.yaml, opens a local test-chat page with a clickable example question under every discovered tool — click one and see a real response come back from the live source, no AI key needed, just local keyword matching to sanity-check the server works — and prints a ready-to-paste connection snippet for Claude Desktop, Cursor, VS Code, and Claude Code. Wiring it into a real AI client is a copy-paste, not a separate step. (Prefer the raw tool list instead? legacy2mcp inspect --config config.yaml.)

legacy2mcp discover does the same for sources that benefit from a review step first (a Postman collection, a HAR capture, …): write a contract, open the same test chat, print the same connection snippet — one command either way.

Have your own WSDL, REST API, website, or codebase instead? legacy2mcp init (no flags) walks you through it — see Generate a config automatically. More demos (a local SOAP service, Docker, a WSDL served by raw URL) are listed in examples/.

[!NOTE]

legacy2mcp introspects your legacy system live — every WSDL operation, every database table, every REST spec it can find — and builds a real JSON Schema for each tool from it. Every MCP tool call is schema-validated before it reaches your backend, write operations are excluded by default, and every call is audit-logged. No hand-written adapter code, no hand-maintained schemas, no arbitrary SQL from the LLM.

Contents

  • Install
  • Quick start
  • How it works
  • Why not just write an adapter by hand?
  • Point it at your own WSDL
  • Point it at your own database
  • Point it at your own REST API
  • Generate a config automatically
  • Discover a legacy interface before generating a server
  • Teach your AI coding agent about legacy2mcp
  • Common commands
  • Client support
  • What's handled
  • Safety model
  • Data flow and privacy
  • Use cases
  • Real-world usage
  • Configuration reference
  • Documentation
  • Roadmap
  • Development · Contributing · License

Install

# Full install (recommended)

pip install "legacy2mcp[ai]"

Or the identical, scan-only-ready core -- AI-assisted legacy2mcp init

needs no extra package either way, just an API key at runtime; [ai]

above installs nothing extra today, it's just a stable, familiar name

pip install legacy2mcp

or: uv tool install legacy2mcp · pipx install legacy2mcp

Also published to the [MCP Registry](https://registry.modelcontextprotocol.io/v0.1/servers?search=io.github.bvenkata/legacy2mcp) as io.github.bvenkata/legacy2mcp, so registry-aware MCP clients can discover it directly.

How it works

flowchart LR

WSDL["WSDL / XSD"] --> GEN["legacy2mcp schema generation"] DB["DB schema (allowlisted tables)"] --> GEN GEN --> TOOLS["Typed MCP tools one per operation / table / query"] AGENT["AI agent / MCP client"] -->|tool call| VAL{"schema validation"} TOOLS -. defines .-> VAL VAL -->|invalid args| REJ["rejected, never reaches SOAP/DB"] VAL -->|valid and allowed| BACKEND["SOAP endpoint or database"] BACKEND --> RESP["plain JSON back to the agent"] VAL --> LOG[("audit log")]

SOAP:

  1. Loads the WSDL with zeep, a mature, widely-used Python SOAP client.
  2. For every operation on every port/binding, converts the XSD input type into a JSON Schema (schema/xsd_to_jsonschema.py) — simple types, nested complex types, enums and arrays, recursively, depth-limited for pathological WSDLs.
  3. Registers one MCP tool per operation, named _ .
  4. On a tool call: validates arguments with jsonschema (schemas use additionalProperties: false), calls the operation via zeep, serializes the response to plain JSON, and writes an audit entry.

DB:

  1. Connects with the dialect's driver (psycopg / pyodbc / oracledb, imported lazily) and introspects the live column types for each allowlisted table (adapters/db_dialects.py) into JSON Schema (schema/sql_to_jsonschema.py).
  2. Registers select_ / insert_ per allowlisted table-and-operation, plus query_ per named query in config.
  3. On a tool call: validates arguments, builds SQL from the allowlisted table/columns (or runs the config-supplied named query) using one dialect-neutral :param placeholder convention, executes it, and writes an audit entry. The LLM never sees or writes SQL text.
  4. Operations whose names look like writes are excluded unless allow_write_operations: true.

REST:

  1. There's no live schema to introspect a plain REST API from the way there is a WSDL or a DB catalog, so the endpoint list (method, path, typed params) comes from config -- hand-written, or generated by legacy2mcp init's OpenAPI/Swagger discovery or source-code scan.
  2. Registers one MCP tool per allowlisted endpoint, named _ .
  3. On a tool call: validates arguments, splits them into path/query/body by each param's declared location, substitutes {param} placeholders into the URL, and calls it with requests -- auth applied per the adapter's auth config (basic/bearer/none).
  4. Endpoints marked write: true are excluded unless allow_write_operations: true. legacy2mcp init sets that flag by default on non-GET endpoints and on endpoints whose names look like writes; in a hand-written config, the HTTP method alone does not hide an endpoint.

Why not just write an adapter by hand?

Because a hand-written adapter is a second copy of your system's schema that nobody remembers to update. The first time a WSDL operation's signature shifts or a column changes, your tool's JSON Schema silently drifts from reality — and an LLM calling it finds out by sending arguments that are wrong in a way nothing catches, or by getting a confusing runtime error from deep inside the SOAP/DB client. legacy2mcp builds the schema from the live system every time it starts, so a drifted call fails at validation, before it ever reaches your backend — not after.

Hand-written adapter (FastMCP / raw SDK)Generic OpenAPI-to-MCP proxylegacy2mcp
Schema sourceTyped by hand, per toolThe OpenAPI spec, if one existsThe live WSDL / DB schema, or a discovered OpenAPI spec
Can drift from the real systemYes — nothing re-checks itOnly if the spec itself is staleNo — rebuilt from the live source at startup
Covers SOAP / a databaseYou write that client code yourselfNo — REST/OpenAPI onlyYes, plus REST and plain websites
Write operations hidden by defaultNo — you remember to gate each oneNo — usually exposes everything the spec definesYes — explicit allow_write_operations opt-in
Audit log of every callDIYUsually noBuilt in
Time to a working serverHours to days, per systemMinutes, for a REST API with a specMinutes — legacy2mcp init

Point it at your own WSDL

# config.yaml

server: name: my-legacy-mcp

adapters:

  • id: legacy type: soap config: wsdl_url: "https://service.example.com/LegacyService?wsdl" auth: type: basic username: "svc-account" password_env: "SERVICE_PASSWORD" # value read from the environment, never the file allow_write_operations: false # Create*/Update*/Delete*/… stay hidden include_operations: ["GetRecord", "GetRecordDetails", "SearchRecords"]

security: audit: enabled: true path: "./legacy2mcp-audit.log"

export SERVICE_PASSWORD=...

legacy2mcp inspect --config config.yaml # review the generated tools legacy2mcp run --config config.yaml

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

Ask PopNx