How I built a daily research pipeline with Hermes Agent that finds SMEs with legacy APIs, scores them on MCP readiness, and pre-audits their public API surface — all running autonomously on my own infrastructure.
The Problem: Finding Companies That Need MCP
MCP (Model Context Protocol) is the emerging standard for connecting legacy APIs, databases, and manual workflows to AI agents. But finding companies that actually need MCP integration — and that have the budget and readiness to act — is a manual, time-consuming sales process.
I'm constantly thinking about where to focus my help and services. My problem was simple: I needed a way to find prospects daily without spending hours on LinkedIn and Reddit. My problem was simple: **I needed a way to find prospects daily without spending hours on LinkedIn and Reddit.
Enter Hermes Agent.
What I Built
A fully autonomous MCP Lead Generation & Pre-Audit System that runs daily on my own infrastructure:
- Every day at 10:00 AM, Hermes Agent researches LinkedIn, Reddit, GitHub, Product Hunt, and tech blogs looking for SMEs that show signs of systems fragmentation
- It scores each prospect against a 13-point MCP Readiness Checklist
- For high-scoring prospects, it pre-audits their public API documentation to identify MCP integration opportunities
- It emails me a structured report with company name, contact info, score, and specific MCP tools that could be built
The result is a daily pipeline of warm, pre-vetted leads — each one with a concrete MCP action plan ready to go.
The MCP Readiness Checklist
I designed a 13-question scoring system based on four dimensions:
1. Systems Fragmentation (3 pts)
- Uses 5+ SaaS tools that don't talk to each other
- Has proprietary/legacy internal APIs or siloed databases
- Uses Zapier/Make for integrations (bonus if complaining about cost)
2. Manual Work & Friction (4 pts)
- Someone copies/pastes data between systems regularly
- Workflows that "should be automated" but aren't
- Data conflicts between systems
- A "data person" doing undocumented manual magic
3. Scale & Growth (3 pts)
- Each new client adds manual work hours
- Wants automation but no devs available
- Planning 50%+ growth in the next 12 months
4. Budget & Readiness (3 pts)
- Already spending €500+/month on SaaS
- Has budget for consulting (€20-40k)
- Has a CTO or VP Ops champion
8+ points = High priority. 5-7 = Warm. 0-4 = Skip.
How Hermes Agent Runs the Pipeline
The system is a Hermes Agent cron job — a self-contained prompt that the agent executes on schedule. Here's how it works:
Phase 1: Parallel Research
Hermes Agent launches parallel research tasks across multiple sources:
delegate_task(tasks=[
{"goal": "Search LinkedIn for operations managers
at SMEs mentioning 'tool sprawl'..."},
{"goal": "Scan Reddit r/SaaS, r/smallbusiness
for integration pain points..."},
{"goal": "Check ProductHunt and tech blogs
for companies with obvious API needs..."},
])
Phase 2: Scoring & Analysis
Each prospect is evaluated against the 13-point checklist. The agent reads company websites, checks their API docs, looks for GitHub repos, and builds a complete profile.
Phase 3: Pre-Audit (The Secret Weapon)
For companies with public API documentation or GitHub repos, the agent performs a deeper analysis:
- API surface mapping — What endpoints exist? Auth model? Data formats?
- MCP tool identification — Which endpoints would make good MCP tools?
- Complexity estimation — Easy / Medium / Hard to build MCP wrappers
- Security considerations — What needs attention before building
This transforms a cold lead into a warm prospect with a concrete MCP proposal ready to present.
Real Results: Two Pre-Audited Companies
On its first run, the system found and pre-audited two LATAM tech companies:
1. Cobre (Fintech, Colombia) — Score: 9/13
Signal: API-first payments platform with fragmented client systems.
The agent found their API documentation, analyzed ~50 REST endpoints across 18 categories (accounts, payments, FX, checkouts), and identified 5 specific MCP tools that could be built:
-
cobre_crear_contraparte— Register beneficiaries by country/rail -
cobre_ejecutar_pago_local— Execute SPEI/ACH/Bre-B payments -
cobre_crear_cotizacion_fx— Get FX quotes for cross-border -
cobre_ejecutar_pago_internacional— Execute international payments -
cobre_consultar_estado_pago— Track payment status
Key finding: Cobre already has an MCP server via Apidog — but a custom MCP server would be more powerful and fill their SDK gap (no Python/Node.js SDKs exist).
2. Truora (Identity Verification, Colombia) — Score: 7/13
Signal: API-first identity verification with ~120 endpoints across 5 API families.
The agent mapped their entire API surface: Checks API (background checks), Digital Identity (document/facial verification), WhatsApp Engagement (chatbots), Business Rules Engine, and Validator Suite. Suggested 5 MCP tools:
-
truora_check_background— Create background checks per country -
truora_get_check_result— Get verification results with scores -
truora_create_identity_process— Start digital identity validation -
truora_send_whatsapp_message— Send WhatsApp via templates -
truora_list_checks— Query verification history
Key finding: Truora only has iOS SDKs — no Python, Node.js, or Go tooling. An MCP server would fill a critical gap in their developer ecosystem.
The Architecture
The heart of the system is a self-contained Hermes Agent cron job prompt. Here's the structure:
# Create the cron job
hermes cron create \
--schedule "0 10 * * *" \
--prompt "research prospects..."
The prompt instructs Hermes Agent to:
- Research — Use browser and web tools to find SMEs across LinkedIn, Reddit, GitHub, and blogs
- Score — Apply the 13-point MCP Readiness Checklist
- Pre-audit — For READY TO AUDIT companies, visit their API docs and GitHub repos
- Compile — Format everything into a structured plain-text report
-
Deliver — Email via
himalaya template send
cat << 'MAILDELIM' | himalaya template send
From: me@email.com
To: me@email.com
Subject: 🔌 MCP Prospects — [DATE]
═══════════════════════════════════════
1. AUDIT NOW — Company Name
🔧 PRE-AUDIT: READY TO AUDIT
API Docs: https://docs.example.com/
...
🛠️ Suggested MCP tools:
• tool_name — what it does
═══════════════════════════════════════
MAILDELIM
Why Hermes Agent Was the Right Tool
I chose Hermes Agent for three reasons:
Autonomous research — The agent can browse, read, analyze, and make decisions without me in the loop. It's not a script — it reasons about what it finds.
Tool ecosystem — Hermes Agent's built-in browser, web search, and terminal tools let it navigate real websites, parse API docs, and interact with GitHub — just like a human researcher would.
Self-hosted — This runs on my own infrastructure. No API costs, no data leaks to third parties. The prospect data stays mine.
Cron jobs — The built-in scheduler means the system runs itself. I wake up to a fresh lead report every morning.
What's Next
This system is already running daily. My roadmap includes:
- Building the actual MCP servers — Taking the pre-audit output and building the MCP servers for the highest-priority prospects
- Adding more research sources — AngelList, Crunchbase, and Y Combinator companies
- Automated outreach — Integrating with LinkedIn DM or email to send personalized MCP proposals
- Refining the scoring model — Learning from which leads convert and adjusting the checklist weights
Try It Yourself
If you're running Hermes Agent, you can build something similar in a few hours:
- Define your scoring criteria
- Write a research prompt (the agent handles the execution)
- Create a daily cron job
- Sit back and watch the leads roll in
The hardest part isn't the technology — it's knowing what signals to look for. That's where your domain expertise comes in.
Built with Hermes Agent — the open-source agentic system that runs on your own infrastructure.
🔗 **Full code and prompts:* github.com/nujovich/hermes-mcp-lead-gen*
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