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memsprout vs GitMir

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

memsprout compared with GitMir
Detailmemsprout logo memsproutGitMir logo GitMir
What it doesShared AI-context layer for teams AI model of your product's business logic accessible to people and AI agents
StageStartup Not given
FoundedNot given Not given
Based inNot given GB
Pricing modelFreemium Freemium
PricingIndividual: $10/month. Team: $15 per user per month. Enterprise: Custom pricing. All plans start with 14-day free trial. Free: 10,000 starting credits plus 1,000 per month. Engineering: $29 per active developer per month with 30,000 pooled credits each month. GitMir Vibe: $9 per person per month. Cloud Compute: $99 per project per month. MeetAI: $49 per project per month. GoBots: $99 per venture per month. Market: $49
Key features
  • Connect any MCP client
  • Space-based access control with owner, editor, and viewer roles
  • Version history on every memory
  • Per-memory attribution and provenance tracking
  • Row-level security in Postgres
  • Topic-based organization within Spaces
  • Works with Cursor, Claude Code, Copilot, ChatGPT
  • Priority support on Team and Enterprise plans
  • Personal and Shared Spaces
  • Builds features, rules and customer paths and keeps them current with every push
  • Shows what each commit changed in the business logic, not only in the code
  • Provides change impact analysis before merge showing what could break
  • Checks PRDs and specifications against the product
  • Delivers understanding to AI agents over MCP
  • Runs locally on your machine with GMM Local
  • Finds risky patterns and problems in the product
  • Enterprise deployment inside your security boundary
  • Integrates with Claude Code, Cursor, Codex and VS Code
  • MCP access for agents with 1-10 credits per answer
What makes it different
  • Tool-agnostic across mixed AI stacks instead of locked to one vendor
  • Works across teams without copy-paste or re-explaining context
  • Person-first design where everyone maintains their own knowledge slice
  • Single-team pricing with no enterprise minimum
  • Shared control through role-based permissions and governance
  • Nearly 3× fewer errors on Benchmark 001 compared to alternatives
  • 8.4K tokens per question instead of 27.4K for competitors
  • Results published and measurable; method is proprietary
  • Reduces AI cost per completed agent action from $0.35 to $0.08
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)3 −1 (down) since last check27 no change since last check
Trust Flow (Majestic)13
Citation Flow (Majestic)2728
Referring domains (Majestic)7150

5 details filled in for both companies.

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