Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Classify a job title into department and seniority, and optionally verify the position.
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Pick the AI app you use, then copy the settings.
APIFY_TOKENValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"contact-classifier": {
"command": "npx",
"args": [
"-y",
"@mambalabsdev/mcp-contact-classifier"
],
"env": {
"APIFY_TOKEN": "your-value"
}
}
}
}Run this in your terminal
claude mcp add contact-classifier --env APIFY_TOKEN=your-value -- npx -y @mambalabsdev/mcp-contact-classifierFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"contact-classifier": {
"command": "npx",
"args": [
"-y",
"@mambalabsdev/mcp-contact-classifier"
],
"env": {
"APIFY_TOKEN": "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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"contact-classifier": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@mambalabsdev/mcp-contact-classifier"
],
"env": {
"APIFY_TOKEN": "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.
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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 7, 2026
The publisher (mambabuilt.com) is not the repo owner (mambalabsdev); someone else may have listed it
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 0 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.
You need to fill in: APIFY_TOKEN
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 (1.2.1) reached the registry 2 days 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, Signoff
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.
Five gates that make an agent's 'done' provable: run them, read the verdict, audit the record.
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MCP server for the Mamba Labs Contact Classifier actor on Apify.
Give it a job title and it returns the department and the seniority level. Give it a name and a company domain too, and it also checks whether that person is still listed on their employer's own website. The classification is a deterministic rule table, so it needs no API key and returns the same answer for the same title every time.
npx -y @mambalabsdev/mcp-contact-classifier
{
"mcpServers": { "mamba-contact-classifier": { "command": "npx", "args": ["-y", "@mambalabsdev/mcp-contact-classifier"], "env": { "APIFY_TOKEN": "your-apify-token" } } } }
Get an Apify token at console.apify.com/account/integrations.
classify_contactOne contact in, one classified row out. Only the job title is required.
| Input | Type | Required | Notes |
|---|---|---|---|
job_title | string | yes | The contact's job title, exactly as you hold it. Classified by deterministic rules with no API key needed. |
full_name | string | no | Only needed for position verification. Classification works without it. This name is never sent to any language model. |
company_domain | string | no | Only needed for position verification. The company's website domain, with or without https. |
verify_position | boolean | no | Check whether the person is still listed on their employer's own website. Adds roughly 3 seconds and 9 requests per contact, and needs both the name and the domain. Default false. |
use_llm_fallback | boolean | no | Sends titles the rules cannot place to your own model, using the LLM_API_KEY secret environment variable on your own copy of the actor. Only the title is sent, never the person's name. Default false. |
llm_provider | enum | no | openai, anthropic or google. Which provider your LLM_API_KEY belongs to. Only read when the LLM fallback is on. Default openai. |
llm_model | string | no | Model id passed straight through to the provider. Only read when the LLM fallback is on. Default gpt-4o-mini. |
skipCache | enum | no | Set to true to ignore cached results and classify from scratch. Default false. |
max_charge_usd | number | no | Optional cost cap in USD for this run. The actor stops before an item that could take its charges past this amount. Omit to rely on the maximum cost per run set in Apify. |
21 flat snake_case fields, one row per contact. department is one of 12, seniority one of 12, and seniority_rank is 1 to 12 so a decision maker filter is a comparison rather than a list of strings. classification_rule names the rule that fired, which is what makes the decision auditable.
With no LLM_API_KEY set, titles the rules cannot place come back null. The row is still returned.
You are charged per contact classified, plus a small actor start fee. The deterministic classification calls no model and no third party API.
| Event | Price | Fires when |
|---|---|---|
apify-actor-start | $0.00005 | Once per run, on start, one event per GB of memory (minimum one). Apify's start event. |
contact-classified | $0.003 (FREE tier), down to $0.00255 on GOLD and above | Once per contact, including a title the rules cannot place. |
Full pricing is on the actor's Apify page. Running this server consumes Apify credits.
The tool starts the actor run and polls it to a finished status, so a run with verify_position on is not cut off at 300 seconds. A run that does not succeed comes back as an error with its run ID and status.
It is a thin client for the Apify actor. It passes your input through and returns the actor's output unchanged. Every behavior described above lives in the actor, not here.
This actor does not discover people. The name and title come from you. It classifies a title and, optionally, checks a name against a page the employer published. To find people in the first place, use People Finder.
Errors are surfaced, never swallowed. An invalid input, an invalid token, an exhausted balance, a timeout, or a run that returns anything other than a dataset all come back as an explicit tool error rather than as an empty result.
The actor is on the Apify Store. This wrapper is MIT licensed.
Built by Mamba Labs