Get MCP Ads vs Cogni
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Get MCP Ads compared with Cogni
| Detail | 
Get MCP Ads | C
Cogni |
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| What it does | Connect your ad accounts to Claude or ChatGPT with 600 tools and 214 media-buying playbooks
| Memory that reasons
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
| US
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| Pricing model | Freemium
| Freemium
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| Pricing | Free: $0/month (1 ad account, 1 seat, 200 tool calls per month, read only). Pro: $29/month (4 ad accounts, 1 seat, unlimited tool calls, reads and writes). Team: $99/month (12 ad accounts, 5 seats, unlimited tool calls, reads and writes). Enterprise: contact for pricing (unlimited ad accounts, 5 sea
| Free plan at $0 USD; Pro plan at $5 USD per month.
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| Key features | - 600 implemented tools across 14 advertising platforms
- 214 media-buying playbooks for analysis and optimization
- Preview-before-apply workflow for all campaign changes
- Per-account granular access control
- Support for 14 advertising and analytics platforms
- Natural language queries against advertising accounts
- AES-256-GCM token encryption before storage
- Bulk ad creation with Google Drive and Dropbox imports
- Google Sheets exports with scheduled automatic refresh
| - Entity-graph spreading activation for cross-vocabulary retrieval
- Works with any LLM model
- No LLM or GPU in retrieval path
- Point-in-time and windowed recall
- Timestamped memories
- Fixed recall cost as memory grows
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| What makes it different | - One URL connection with no local installation required
- Natural conversation interface instead of query language
- Automatic safety with preview and confirmation before changes apply
- Works with multiple AI assistants: Claude, ChatGPT, Cursor, Codex
- Media-buying playbooks guide AI through structured analysis workflows
| - Reaches answers across unrelated documents that share no keywords, where vector search scores zero
- Deterministic retrieval with no model in the path, so results never vary between queries
- Constant per-query cost regardless of memory size, even at 32,000 words
- No infrastructure to run—no vector database, cluster, or GPU needed
- Works with any model, so small local models gain the most from better retrieval
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 15 ▲ +1 (up) since last check | 4 ● no change since last check |
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| Trust Flow (Majestic) | 9 | 2 |
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| Citation Flow (Majestic) | 32 | 21 |
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| Referring domains (Majestic) | 45 | 34 |
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5 details filled in for both companies.
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