Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Waterfall lead enrichment — cascades Apollo, Clearbit, and Hunter for max coverage
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.
APOLLO_API_KEY, CLEARBIT_API_KEY, HUNTER_API_KEYValues 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": {
"leadenrich": {
"command": "uvx",
"args": [
"leadenrich-mcp"
],
"env": {
"APOLLO_API_KEY": "your-value",
"CLEARBIT_API_KEY": "your-value",
"HUNTER_API_KEY": "your-value"
}
}
}
}Run this in your terminal
claude mcp add leadenrich --env APOLLO_API_KEY=your-value --env CLEARBIT_API_KEY=your-value --env HUNTER_API_KEY=your-value -- uvx leadenrich-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"leadenrich": {
"command": "uvx",
"args": [
"leadenrich-mcp"
],
"env": {
"APOLLO_API_KEY": "your-value",
"CLEARBIT_API_KEY": "your-value",
"HUNTER_API_KEY": "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": {
"leadenrich": {
"type": "stdio",
"command": "uvx",
"args": [
"leadenrich-mcp"
],
"env": {
"APOLLO_API_KEY": "your-value",
"CLEARBIT_API_KEY": "your-value",
"HUNTER_API_KEY": "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.
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 registry name was verified with the GitHub account carsonroell-debug, 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.
You need to fill in: APOLLO_API_KEY, CLEARBIT_API_KEY, HUNTER_API_KEY
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 (0.2.0) reached the registry 7 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Foliosio
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.
Read your support inbox, tag conversations and save draft replies from your AI agent. Never sends.
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.
Waterfall lead enrichment for AI agents. Cascades through Apollo, Clearbit, and Hunter to build the most complete lead profile in a single call.
One-click install: Install on MCPize |
pip install leadenrich-mcp
LeadEnrich MCP exposes lead and company enrichment through the Model Context Protocol (MCP), so tools like Claude and Cursor can run enrichment workflows directly. Give it an email, domain, or name and it returns a merged profile with field attribution showing which provider contributed each data point.
pip install leadenrich-mcp
leadenrich-mcp
The server starts on http://localhost:8300/mcp by default.
Add to claude_desktop_config.json:
{
"mcpServers": { "leadenrich": { "url": "http://localhost:8300/mcp" } } }
claude mcp add leadenrich --transport http http://localhost:8300/mcp
| Tool | Description |
|---|---|
enrich_lead | Full waterfall enrichment for a single lead (email, domain, or name+domain) |
find_email | Discover an email from first name + last name + company domain |
enrich_company | Company firmographic data by domain (industry, size, revenue, etc.) |
enrich_batch | Batch enrich up to 25 leads concurrently |
check_usage | Quota, cost tracking, and remaining lookups |
health_check | Server status, configured providers, and cache stats |
LeadEnrich uses a waterfall strategy: each provider fills gaps left by the previous one. When email is known, all providers run concurrently for speed. When only name+domain is provided, Apollo discovers the email first, then Clearbit and Hunter run in parallel.
Input (email / domain / name+domain)
| v +-----------+ +-----------+ +----------+ | Apollo | --> | Clearbit | --> | Hunter | +-----------+ +-----------+ +----------+ | Contact | | Company | | Email | | Company | | Person | | Verify | | LinkedIn | | Firmo | | Domain | +-----------+ +-----------+ +----------+ | | | v v v +------------------------------------------+ | Merged Profile | | 16+ fields with per-field attribution | | Confidence score + lookup cost | +------------------------------------------+
Each field in the result includes attribution so you know exactly which provider it came from. No duplicate API calls thanks to built-in caching.
| Tier | Cost | Details |
|---|---|---|
| Free | $0.00 | 50 lookups/month |
| 1 provider hit | $0.05/lookup | Single provider returned data |
| 2 providers hit | $0.10/lookup | Two providers contributed fields |
| 3 providers hit | $0.15/lookup | Full waterfall, maximum coverage |
pipgit clone https://github.com/carsonlabs/leadenrich-mcp.git
cd leadenrich-mcp pip install -r requirements.txt python main.py
MCP endpoint:
http://localhost:8300/mcp| Variable | Description | Required |
|---|---|---|
APOLLO_API_KEY | Apollo.io API key | No |
CLEARBIT_API_KEY | Clearbit API key | No |
HUNTER_API_KEY | Hunter.io API key | No |
LEADENRICH_API_KEY | Client auth key for usage metering | No |
LEADENRICH_FREE_TIER_LIMIT | Free tier limit (default: 50) | No |
PORT | Server port (default: 8300) | No |
All provider keys are optional. The server uses whichever providers are configured and skips the rest.
Example:
export APOLLO_API_KEY="your-apollo-key"
export CLEARBIT_API_KEY="your-clearbit-key" export HUNTER_API_KEY="your-hunter-key" python main.py
Run directly:
python main.py
Run via FastMCP CLI:
fastmcp run main.py --transport streamable-http --port 8300
enrich_leadInputs:
email (optional): Contact email address (best identifier)domain (optional): Company domain (e.g. "stripe.com")first_name / last_name (optional): Contact name (combine with domain)providers (optional): Limit which providers to useapi_key (optional): Your LeadEnrich API keyReturns merged lead profile with field attribution, confidence score, and lookup cost.
find_emailInputs:
first_name (required): Contact's first namelast_name (required): Contact's last namedomain (required): Company domainReturns discovered email with confidence score and verification status.
enrich_companyInput:
domain (required): Company domainReturns company-level firmographic data: industry, size, revenue, description, location.
enrich_batchInputs:
leads (required): List of lead objects (max 25), each with optional email/domain/nameproviders (optional): Limit which providers to useapi_key (optional): Your LeadEnrich API keyReturns list of enriched profiles with batch summary.
check_usageInput:
api_key (optional): Your LeadEnrich API keyReturns usage stats: lookup count, cost, tier, remaining quota, and cache stats.
health_checkNo input. Returns server status, configured providers, cache stats, and version info.
fastmcp list-tools main.py
fastmcp call-tool main.py health_check '{}' fastmcp call-tool main.py enrich_lead '{"email":"jane@stripe.com"}' fastmcp call-tool main.py find_email '{"first_name":"Jane","last_name":"Smith","domain":"stripe.com"}' fastmcp call-tool main.py enrich_company '{"domain":"stripe.com"}'
This repo includes smithery.yaml for Smithery deployment.
A Dockerfile is included for Railway, Fly.io, and other container hosts.
# Railway
railway up
fly launch fly deploy
Set your provider API keys in your host environment.
Agent (Claude, Cursor, etc.)
-> MCP LeadEnrich MCP Server (this repo) -> Apollo API (contact + company data) -> Clearbit API (person + firmographic data) -> Hunter API (email finding + verification)
This server is a translation layer between MCP tool calls and multiple enrichment provider APIs, with built-in caching, usage metering, and waterfall merge logic.
| Tool | Free | Pro ($29/mo) |
|---|---|---|
enrich_lead | Yes (Hunter only) | Yes (full waterfall: Apollo + Clearbit + Hunter) |
check_usage | Yes | Yes |
health_check | Yes | Yes |
find_email | - | Yes |
enrich_company | - | Yes |
enrich_batch | - | Yes |
Free tier gives you single-provider lookups via Hunter. Pro unlocks the full 3-provider waterfall, email finder, company enrichment, and batch operations.
[Upgrade to Pro on MCPize](https://mcpize.com/mcp/leadenrich-mcp?ref=YHCCR&utm_source=github&utm_medium=readme) — $29/mo or $290/yr.
Built by Freedom Engineers