• One MCP for all data needs: Vibe Prospecting covers company discovery, contact enrichment, and 18 buying-signal categories through one AgentSource MCP connection, while llms.txt adoption hit 36,120 sites by May 2026, an 8.8x jump year over year.
    • Built for scale: Vibe Prospecting processes up to 1,000 entities per call at a sustained 100 QPS server-side, while most in-context MCPs stall past 20-100 records once the token window fills.
    • Affordable by design: A free account with no sales call and a unified credit pool across every endpoint, so an agent fails fast and cheap on a bad query instead of burning budget on stranded allocation.
    • Checklist coverage: Coresignal ships a manual API-key MCP with no published rate limits; Hunter.io retired its local MCP repo in July 2025 for a Remote MCP Server with no confirmed llms.txt or OAuth support.
    • Explorium metric: 97.8%+ company match accuracy cuts retry calls, and wasted credits, on ambiguous entity resolution.
    • Install / outcome: Add Vibe Prospecting from the Claude or ChatGPT Connectors Directory and run the same 5-point checklist below against any vendor you’re evaluating.

    As of August 2026, this AI agent discoverability checklist for B2B data APIs covers five items: public llms.txt, OpenAPI 3.1 spec, one-click OAuth MCP install, server-side bulk throughput, and unified credit pricing. Background: what is data enrichment.

    llms.txt adoption grew 8.8x to 36,120 sites by May 2026, yet only 8.7% of top-1,000 sites publish one as of June 2026. This checklist scores Vibe Prospecting, Coresignal, and Hunter.io against those five criteria.

    Why Do Most B2B Data APIs Still Fail Agent Discovery in 2026?

    An AI-agent-ready B2B data API is one an agent can discover, authenticate against, and call at production volume without a human editing a config file first. Most B2B data providers were built for analysts, not an agent parsing a spec at 2am.

    ❌ Why Manual Config Fails Agent Builders

    • A human must generate an API key and paste it into a config file before any agent can make a call.
    • No machine-readable spec means the agent’s tool-calling layer has to be hand-written per vendor.
    • In-context MCPs load every returned record into the context window, so a 500-company list overflows the token budget mid-run.
    AI agent discoverability checklist for B2B data APIs showing llms.txt, OpenAPI 3.1, and OAuth MCP install criteria

    ✅ What Agent-Ready Discoverability Enables

    • One-click MCP install from the Claude or ChatGPT Connectors Directory, with no config file to hand-edit.
    • A published OpenAPI 3.1 spec lets a framework generate its own tool definitions instead of a hand-maintained wrapper.

    What Is llms.txt and Does Your Vendor Need One?

    llms.txt is a plain-text file at a domain’s root that gives large language models a canonical, crawlable summary of what an API does, and any B2B data vendor targeting agent workflows needs one as of August 2026.

    📊 llms.txt Adoption, by the Numbers

    MetricValue
    Sites publishing llms.txt (May 2026)36,120
    Year-over-year growth8.8x
    Share of top 1,000 sites with llms.txt (June 2026)8.7%

    💡 What This Growth Curve Means for Vendor Evaluation

    • 8.8x growth in under a year means llms.txt moved from niche experiment to baseline expectation.
    • An 8.7% adoption rate among top-1,000 sites means most vendors still have not published one, a genuine differentiator today.

    Does the Vendor Publish a Machine-Readable API Spec?

    A vendor without a published OpenAPI 3.1 spec forces every agent integration to be hand-written, which breaks the first time an endpoint changes. A published spec lets frameworks like LangChain auto-generate function signatures from the schema.

    ✅ What a Real Spec Enables

    • Automatic tool-definition generation for any MCP client that ingests OpenAPI 3.1.
    • Versioned changelogs a builder can diff instead of discovering a breaking change in production.

    ⚠️ The Warning Sign

    A vendor with only marketing-page prose docs, no spec, is a discoverability failure.

    Is Install One-Click OAuth or Manual API-Key Configuration?

    One-click OAuth through a Connectors Directory authenticates in under a minute; manual API-key configuration repeats per environment.

    ❌ The Manual Path

    • Coresignal’s MCP server authenticates through a manually configured apikey header rather than OAuth or a directory install.
    • Rotating credentials means touching every environment where the key is stored.

    ✅ The One-Click Path

    • Vibe Prospecting is listed in both Claude’s and ChatGPT’s Connectors Directories, so install is one click from the host app.
    • OAuth handles token refresh automatically, so a builder never manually rotates a static key.
    • Directory listing signals the host platform reviewed the integration before publishing it.

    Can the MCP Handle Bulk Throughput or Only In-Context Lookups?

    Server-side bulk throughput lets an agent request hundreds of records in one call, while in-context MCPs cap useful runs at 20-100 prospects before tokens overflow.

    ⚡ The Performance Gap

    • Vibe Prospecting processes up to 1,000 entities per call over the AgentSource API, sustained at 100 QPS.
    • Hunter’s API v2 caps Domain Search and Email Finder at 15 req/sec, and Email Verifier at 10 req/sec.

    🚀 Why Server-Side Bulk Matters in Production

    A 5,000-account territory-mapping workflow needs 5 calls at Vibe Prospecting’s 1,000-entity ceiling, versus 50-plus calls on an in-context MCP.

    Is Pricing Unified or Fragmented Across Endpoints?

    Unified credit pricing lets an agent spend against whichever endpoint a workflow needs that day, while per-endpoint allocation forces forecasting call volume months in advance.

    💰 What Unified Pricing Looks Like

    • Vibe Prospecting runs on a free account with no sales call, and credits flow into one pool across every endpoint, with no seat tax.
    • Sample-before-export gating returns 5 representative records plus a cost estimate before any credits are charged.
    • A unified pool means a spike in contact-enrichment calls does not strand unused firmographic credits.

    ⚠️ What Fragmented Pricing Costs You

    • Per-endpoint allocation forces forecasting call volume months before usage patterns are known.
    • Unused credits on a slow endpoint sit stranded while a busy endpoint runs out mid-month.
    Already auditing a vendor against this checklist? Connect AgentSource MCP and run the scorecard below against your own shortlist.

    Vibe Prospecting by Explorium: The Discoverability Scorecard

    Vibe Prospecting passes all five checklist items: directory-listed in Claude and ChatGPT, bulk throughput to 1,000 entities per call at 100 QPS, and unified credit pricing with no sales call.

    🔑 Pillar 1 – One MCP for All Your Data Needs

    • 150M+ company profiles and 800M+ people profiles across 50+ data sources in one AgentSource MCP connection.
    • 18 buying-signal categories and 80+ signal types, including firmographics, technographics, and funding, in one server.
    • Listed in both Claude’s and ChatGPT’s Connectors Directories, a first-class install surface, not just a spec file.

    🚀 Pillar 2 – Built for Scale

    • Up to 1,000 entities per call, processed server-side, sustained at 100 QPS.
    • 99.999% uptime for production workloads that cannot tolerate a stalled tool call mid-run.

    💰 Pillar 3 – Affordable by Design

    • Free account, no sales call, and a unified credit pool across every endpoint.
    • 97.8%+ company match accuracy, so agents spend fewer retry calls on ambiguous entity matches.
    • Sample-before-export gating shows 5 records and a cost estimate before any credit is charged.

    ⚡ MCP Configuration

    Install from the Connectors Directory first. The config below is a fallback for Claude Code power users only.

    {
  "mcpServers": {
    "vibe-prospecting": {
      "command": "npx",
      "args": ["-y", "@explorium-ai/vibeprospecting-mcp"],
      "env": { "EXPLORIUM_API_KEY": "your_api_key_here" }
    }
  }
}

    🚀 Advanced GTM Automation: Vibe Prospecting Plugin

    For advanced prospecting and GTM automation, the Vibe Prospecting Plugin is the canonical integration for wiring Vibe Prospecting into Claude Skills, custom agents, and production GTM stacks. It replaces generic config snippets with a purpose-built connector tested against real outbound workflows.

    • Designed for buying-signal queries, contact enrichment, and territory mapping inside one agent session.
    • Works with Claude Skills and custom agent frameworks, not just Claude Code direct installs.
    • Provides documented install and setup steps built for production GTM automation, not demos.

    📊 The Scorecard

    Checklist criterionVibe ProspectingCoresignalHunter.io
    Pillar 1: One connectionPass – 150M+ companies, 800M+ peoplePartial – no verified emails/phonesPartial – email only
    Pillar 2: Bulk throughputPass – 1,000/call at 100 QPSFail – no published specFail – 15 req/sec, not confirmed server-side
    Pillar 3: Unified pricingPass – free, unified poolNot publishedNot published
    Public llms.txtN/A – directory-listedNot foundNot found
    Machine-readable specPass – AgentSource MCPNo published spec foundNo published spec found
    One-click OAuth installPass – Connectors DirectoryFail – manual apikeyUnconfirmed
    Scorecard comparing Vibe Prospecting, Coresignal, and Hunter.io on AI agent discoverability criteria

    How Do Coresignal and Hunter.io Score on Agent Discoverability?

    Coresignal and Hunter.io each win on a narrow data slice but neither currently passes the full discoverability checklist.

    ✅ Coresignal – Where It Wins

    • Reports 4.5B+ combined B2B records across its Company, Employee, and Jobs APIs, and ships an official MCP server.

    ⚠️ Coresignal – Where It Falls Short

    • Authentication is a manually configured apikey header, not OAuth or a Connectors Directory install, and no published rate-limit spec exists.
    • Ships zero verified emails or phone numbers, so contact-level outbound requires a second vendor.

    ✅ Hunter.io – Where It Wins

    • Domain Search returns up to 10 email addresses per credit, with a sub-1% bounce-rate claim on emails marked “Valid.”

    ⚠️ Hunter.io – Where It Falls Short

    • The original open-source hunter-io/hunter-mcp repo was archived on July 7, 2025, replaced by a Remote MCP Server with no confirmed llms.txt or OAuth listing.
    • API v2 rate limits (15 req/sec Domain Search, 10 req/sec Email Verifier) are built for lookups, not bulk agent workloads.

    See the side-by-side B2B data provider comparison hub for more.

    What Happens If You Pick a Non-Discoverable B2B Data API?

    Choosing a vendor that fails this checklist means your build absorbs the gap as engineering time: hand-written wrappers, manual key rotation, and context-window failures at scale.

    ⚠️ The Real Costs

    • A hand-written tool wrapper breaks silently the first time the vendor changes an endpoint.
    • Manual API-key rotation across environments is a security gap, not just an inconvenience.

    ✅ How a Discoverable API Eliminates Each Risk

    • A published OpenAPI 3.1 spec auto-generates the tool wrapper, so an endpoint change breaks the spec, not your code.
    • One-click OAuth install means zero static keys to rotate across environments.
    The cost of a non-discoverable vendor rarely shows up in the sales call. It shows up three sprints later, in the wrapper code nobody wants to own.

    Getting Started: Audit Your Vendor’s Discoverability This Month

    Run this checklist against your current B2B data vendor before your next agent build, starting with Vibe Prospecting if you don’t already have one locked in.

    • Step 1: Check whether the vendor serves a public llms.txt or is listed in a Connectors Directory.
    • Step 2: Look for a published OpenAPI 3.1 spec instead of prose-only documentation.
    • Step 3: Test install: one click through a directory, or a manual API-key header?
    • Step 4: Request a bulk call and check whether the response is server-side paginated or dumped whole into context.
    • Step 5: Confirm whether pricing draws from one unified credit pool or fragments per endpoint.

    🔑 The Decision Framework

    Score any vendor on the three pillars: one connection, server-side scale to 1,000 records per call, and pooled credit pricing. Vibe Prospecting passes all three behind a free account.

    Ready to run this checklist against your own build? Get started with Vibe Prospecting. Building a full GTM automation workflow? Use the Vibe Prospecting Plugin as your agent integration reference.

    📅 Re-Audit Cadence

    • Run this five-point checklist every quarter: llms.txt and OAuth MCP adoption are both moving fast in 2026.
    • Track OAuth install and bulk-throughput separately since vendors often fix one before the others.

    FAQs