# Landbase vs MCP Search (MCP Stack)

Landbase records 76,178 monthly visits with +32.5% month-over-month growth and Paid (usage-based credits) pricing. MCP Search (MCP Stack) records 0 monthly visits with 0% growth and Paid pricing.

| Metric | [Landbase](https://openaitools.app/tool/landbase) | [MCP Search (MCP Stack)](https://openaitools.app/tool/mcp-stack) |
| :--- | :--- | :--- |
| Website URL | https://www.landbase.com | https://mcp-stack.com |
| Categories | AI Lead Generation, AI Cold Calling, AI Email Generator, AI Email Marketing | AI Marketing, AI Agent, AI Sales Assistant, AI Lead Generation |
| Pricing Model | Paid (usage-based credits) | Paid |
| Monthly Visits | 76,178 | 0 |
| MoM Growth Rate | +32.5% | 0% |
| Primary Market | United States | Global |
| Direct Visits | 19,155 | 0 |
| Review Score | 4.3 | 4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Landbase

Landbase targets revenue operations, sales, marketing and growth teams that need to define and reach a market without stitching together several data and enrichment vendors. Its database covers 300M+ contacts with more than 1,500 enrichment fields, and the platform layers on targeting, qualification and enrichment as three connected steps: map the addressable market, keep only accounts matching exact ICP criteria, then enrich contacts with verified emails and mobile numbers.

Its differentiator is agentic search over live signals. A prompt such as 'find US SaaS companies with $10M–50M ARR using Salesforce and HubSpot, with 50+ engineers' is executed in seconds, along with filters for tech stack changes, recent job postings, funding events and pipeline exclusion. Lookalike modeling finds companies similar to past closed-won accounts, AI qualification scores and verifies accounts automatically, and AI agents gather harder-to-source market insights. The pricing model is deliberately usage-based: pay per verified result, with unverified misses costing nothing.

Landbase also ships a CLI designed to be pasted into coding agents like Claude Code or Codex, so GTM data work can happen inside the AI tool a team already uses. It has been recognised as a Gartner Cool Vendor and has raised a $30M Series A, and it publishes research such as GTMBench and maintains a developer doc center and an education hub called Landbase University.

**Pricing & Plans:** Usage-based credits with a free entry point. New accounts get 1,000 credits (or $49 of free credits) with no credit card required. Paid bundles start at $499/month for 15,000 credits, $1,999/month for 75,000 credits and $4,999/month for 200,000 credits, with enterprise rates on request. Searches and lookalike expansion are free, email enrichment costs 1 credit (~$0.033) and phone enrichment 10 credits (~$0.33); unverified results are never charged.

- **Agentic natural-language search:** Describe your ideal account profile in plain English and get a verified, exportable audience back in seconds, including complex boolean and department-level headcount filters.
- **300M+ contact B2B database:** Access a large, continuously refreshed contact graph with 1,500+ enrichment fields spanning firmographics, technographics, hiring, funding and more.
- **Real-time buying signals:** Track tech stack changes, job postings, funding events and other intent signals to prioritise accounts showing active buyer interest.
- **Lookalike modeling:** Find companies that resemble your best closed-won customers, with pipeline exclusion so you never re-target accounts already in play.
- **AI qualification and enrichment:** Automatically verify, score and enrich accounts, routing through 20+ data providers so you only pay for results that check out.

**Strengths:** Natural-language agentic search replaces multi-step list building; Large 300M+ contact database with 1,500+ enrichment fields; Pay-per-verified-result pricing means unverified misses are free; CLI and MCP-style agent integration fit modern AI workflows

**Limitations:** Credit bundles are priced for teams, so solo users may find entry costs high; Requires learning prompt-based workflows rather than familiar filter UIs; Phone enrichment credits are relatively expensive per verified number

[Profile (Markdown)](https://openaitools.app/tool/landbase.md)

## MCP Search (MCP Stack)

MCP Search, live on the mcp-stack.com domain, targets a specific and often underserved job: producing very fine-grained B2B prospect lists for the French market rather than running a global people search. Instead of stacking dozens of filters, you describe your target in a sentence — for example, sales directors who graduated from an engineering school, have worked in manufacturing for at least three years, and are employed at companies that are still active. The engine cross-references legal registry records (INSEE, Infogreffe, BODACC), verified Google Maps listings, public LinkedIn company profiles, open web contact data and financial filings to return a structured list.

The dataset is positioned as a pre-crossed French prospecting base: roughly 27 million legal entities, about 29 million profiles and professional experiences, and around 1.4 million establishment-level records usable in the same query. Job-posting signals from boards such as LinkedIn, Welcome to the Jungle, Pôle emploi and Indeed are announced as coming next.

The product is currently in a waitlist phase with a September launch; the company states that the MCP connector for Claude, Grok or home-built agents is not yet publicly callable and will expose the same France-first list engine when it opens. It positions itself against Apollo (global outbound) and Clay (multi-provider enrichment) rather than against infrastructure tooling. MCP Search is an independent product and is not produced or endorsed by Anthropic, xAI or any model provider.

**Pricing & Plans:** Pricing is not published on the current site. The product is in a waitlist phase ahead of a September launch, and no public plan, trial or per-seat figure is listed yet — check the site for updates when the product opens.

- **One-sentence list building:** Describe your target in plain French and get a cross-referenced list, instead of stacking 8+ filters across NAF codes, revenue thresholds and tenure.
- **Multi-source French data:** Crosses legal registry records (SIREN/SIRET, officers, financials), Google Maps establishments, public LinkedIn company data and open web contacts.
- **Large FR-first coverage:** Around 27M legal entities, roughly 29M profiles and experiences, and about 1.4M establishment records accessible within the same query intention.
- **MCP connector for AI agents:** An MCP endpoint designed so Claude, Grok or a custom agent can run the same fine-grained French account queries, planned for public release at launch.
- **Direct competitor framing:** Explicitly positioned against Apollo-style global people search and Clay-style enrichment workflows, focusing on crossed French list building as the core job.

**Strengths:** Focuses on a genuinely hard problem: fine-grained, cross-referenced French B2B lists rather than generic global people search; Aggregates several authoritative French sources (legal registry, Maps, LinkedIn, financials) into a single intention-based query; Plans an MCP connector so the same list engine is callable by AI agents; Transparent comparison pages against Apollo, Clay and French data providers

**Limitations:** Currently in a waitlist phase, so the core product and MCP tools are not yet publicly usable; No public pricing published, which makes budgeting hard to plan; Coverage is France-specific, so it is not suitable for multi-country outbound

[Profile (Markdown)](https://openaitools.app/tool/mcp-stack.md)

## Frequently Asked Questions

### How do Landbase and MCP Search (MCP Stack) compare in monthly traffic?

Landbase has 76,178 monthly visits, while MCP Search (MCP Stack) has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Landbase has a month-over-month growth rate of +32.5%; MCP Search (MCP Stack) has 0%.

### How does pricing compare?

Landbase: Paid (usage-based credits). Usage-based credits with a free entry point. New accounts get 1,000 credits (or $49 of free credits) with no credit card required. Paid bundles start at $499/month for 15,000 credits, $1,999/month for 75,000 credits and $4,999/month for 200,000 credits, with enterprise rates on request. Searches and lookalike expansion are free, email enrichment costs 1 credit (~$0.033) and phone enrichment 10 credits (~$0.33); unverified results are never charged. MCP Search (MCP Stack): Paid. Pricing is not published on the current site. The product is in a waitlist phase ahead of a September launch, and no public plan, trial or per-seat figure is listed yet — check the site for updates when the product opens.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Instantly](https://openaitools.app/tool/instantly) | 2,336,279 | +6% | Paid, Contact for Pricing | Sales engagement platform with AI agents for lead finding, outreach and deliverability | [.md](https://openaitools.app/tool/instantly.md) |
| 2 | [Clay](https://openaitools.app/tool/clay-2-0) | 1,267,465 | -2.7% | Freemium, Free Trial, Contact for Pricing | Build GTM systems that turn data into revenue | [.md](https://openaitools.app/tool/clay-2-0.md) |
| 3 | [Smartlead](https://openaitools.app/tool/smartlead-ai) | 952,377 | +4.3% | Free Trial, Paid | AI-native cold email platform for scaling outbound without limits | [.md](https://openaitools.app/tool/smartlead-ai.md) |
| 4 | [Success.ai](https://openaitools.app/tool/success-ai) | 547,073 | +6.3% | Freemium, Free Trial | AI sales platform for unlimited B2B leads and outreach | [.md](https://openaitools.app/tool/success-ai.md) |
| 5 | [MailTester.Ninja](https://openaitools.app/tool/mailtester-ninja) | 452,787 | -10% | Freemium | Real-time email verification and email finding that never stores your data | [.md](https://openaitools.app/tool/mailtester-ninja.md) |
| 6 | [Monaco](https://openaitools.app/tool/monaco) | 195,703 | +10.6% | Paid | The AI revenue engine that replaces your CRM | [.md](https://openaitools.app/tool/monaco.md) |
| 7 | [Reply.io](https://openaitools.app/tool/reply-io) | 193,261 | -1.7% | Free Trial, Paid, Contact for Pricing | AI sales engagement and cold email outreach on autopilot | [.md](https://openaitools.app/tool/reply-io.md) |
| 8 | [AI Ark](https://openaitools.app/tool/ai-ark) | 90,788 | -30.7% | Freemium, Contact for Pricing | AI-powered B2B data platform for finding verified contacts, companies, and lookalike audiences | [.md](https://openaitools.app/tool/ai-ark.md) |
| 9 | [Enginy](https://openaitools.app/tool/enginy) | 68,199 | +3.8% | Contact for Pricing | Your all-in-one AI sales edge for smarter B2B outreach | [.md](https://openaitools.app/tool/enginy.md) |
| 10 | [Clodura.AI](https://openaitools.app/tool/clodura-ai) | 48,655 | -12.6% | Free Trial, Contact for Pricing | GenAI go-to-market platform from database to deal closure | [.md](https://openaitools.app/tool/clodura-ai.md) |

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Source: https://openaitools.app/compare/landbase-vs-mcp-stack

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