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BaseMouse logoBaseMouse
vs
widemem logowidemem

BaseMouse vs widemem: Which is Better in 2026?

A comprehensive comparison of BaseMouse and widemem covering features, pricing, use cases, and which tool is the right choice for your needs.

⚡ Quick Verdict

Choose BaseMouse if:

  • You need a broader feature set (8 features vs 6)
  • You need single remote mcp server at one endpoint for every registered tool or shared read/write memory across claude code, cursor, codex, and grok

Choose widemem if:

  • You need local-first by default — sqlite plus faiss, no services to operate or importance-scored memory rather than similarity retrieval alone

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BaseMouse vs widemem: At a Glance

Attribute
BaseMouse
widemem
Pricing Model
Freemium
Open Source
Starting Price
Starting at Open core: the import-and-serve engine is free and MIT-licensed, self-hostable with no license key and nothing phoning home. A paid hosted version adds running, billing, and support, billed through Stripe; the hosted plan figures are rendered client-side and are not published in the page source.
Free to use
Free Tier
✓ Yes
✓ Yes
Category
AI Agent Infrastructure
AI Agent Infrastructure
Features Count
8 features
6 features
Shared Features
0 features in common

Pricing Comparison: BaseMouse vs widemem

Understanding the pricing differences between BaseMouse and widemem is crucial for making the right choice. Here's how their plans compare side by side.

BaseMouse Pricing

PlanOpen core: the import-and-serve engine is free and MIT-licensed, self-hostable with no license key and nothing phoning home. A paid hosted version adds running, billing, and support, billed through Stripe; the hosted plan figures are rendered client-side and are not published in the page source.
View full BaseMouse pricing →

widemem Pricing

The library is Apache 2.0 and free forever, with the full feature set and every provider — the vendor states explicitly that there is no gated open-core play and that paid tiers are about hostingSee website
Self-hosted (your VPC or Kubernetes, plus a named SLA on bug fixes and upgrade support)See website
EnterpriseCustom
View full widemem pricing →

💡 Pricing takeaway: Both BaseMouse and widemem offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.

Feature-by-Feature Comparison

Here's how every feature from BaseMouse and widemem stacks up.

Feature
BaseMouse
widemem
Single remote MCP server at one endpoint for every registered tool
Shared read/write memory across Claude Code, Cursor, Codex, and Grok
Every answer carries its source, a tamper-evident fingerprint, and recency
get_context_pack returns an agent-ready bundle with citations
Version history preserved — nothing silently overwritten, deletions stay on record
Re-import a folder without creating duplicates, with a failure report
Public demo corpus browsable without a key
MIT-licensed self-hostable core
Local-first by default — SQLite plus FAISS, no services to operate
Importance-scored memory rather than similarity retrieval alone
Auditable recall path for regulated and high-stakes deployments
Air-gap capable out of the box
Full Apache-2.0 feature set on every tier, including the free one
Python 3.10+ library, currently at v1.5.0

What Makes Each Tool Unique

🔵 Unique to BaseMouse

Features available in BaseMouse but not in widemem:

  • Single remote MCP server at one endpoint for every registered tool
  • Shared read/write memory across Claude Code, Cursor, Codex, and Grok
  • Every answer carries its source, a tamper-evident fingerprint, and recency
  • get_context_pack returns an agent-ready bundle with citations
  • Version history preserved — nothing silently overwritten, deletions stay on record
  • Re-import a folder without creating duplicates, with a failure report
  • Public demo corpus browsable without a key
  • MIT-licensed self-hostable core

🟣 Unique to widemem

Features available in widemem but not in BaseMouse:

  • Local-first by default — SQLite plus FAISS, no services to operate
  • Importance-scored memory rather than similarity retrieval alone
  • Auditable recall path for regulated and high-stakes deployments
  • Air-gap capable out of the box
  • Full Apache-2.0 feature set on every tier, including the free one
  • Python 3.10+ library, currently at v1.5.0

Use Case Recommendations

Best for: BaseMouse

BaseMouse gives AI agents one shared, versioned memory across Claude Code, Cursor, Codex, and Grok through a single remote MCP server. The problem it names is familiar to anyone using more than one coding agent: project context ends up trapped per tool — a CLAUDE.md here, a Cursor rules file there — and the whole project gets re-explained to every new agent. BaseMouse replaces that with one corpus every registered tool reads from and writes to, so whatever an agent learns in one tool is available to an agent in another, even a different vendor; only the live chat stays inside each tool. Setup is a folder of documents pointed at the service, which reads them, keeps every version, and labels them for retrieval, with re-imports that do not duplicate and a clear report on any file that fails to import. Retrieval returns the most relevant passages with source, a tamper-evident fingerprint, and recency, ready to drop into a prompt — and a get_context_pack tool returns an agent-shaped bundle with citations. Governance is a first-class concern: every change is recorded, nothing is silently overwritten, and even deletions stay on the record, so you can always answer where an answer came from and what changed since. The model is open core — the engine that imports documents and serves sourced answers is free and MIT-licensed and self-hostable with nothing phoning home, while the paid hosted version handles running, billing, and support.

Ideal use cases:

  • Teams or individuals who need single remote mcp server at one endpoint for every registered tool
  • Teams or individuals who need shared read/write memory across claude code, cursor, codex, and grok
  • Teams or individuals who need every answer carries its source, a tamper-evident fingerprint, and recency
  • Teams or individuals who need get_context_pack returns an agent-ready bundle with citations
  • Anyone focused on mcp workflows
  • Anyone focused on agent-memory workflows
Try BaseMouse

Best for: widemem

widemem is an Apache-2.0 memory layer for LLM agents built around the premise that an agent which forgets selectively is worse than useless in domains where a wrong recall is expensive. It is local-first: the default deployment is a Python library backed by SQLite and FAISS, with no services to stand up and nothing to page, and it is capable of running air-gapped out of the box. The three properties the project foregrounds are local-first storage, importance scoring and auditability. Importance scoring is the part that distinguishes it from a plain vector store — rather than embedding everything and retrieving by similarity alone, memories carry a scored notion of what matters, so an agent retains the facts it cannot afford to lose rather than whatever happens to be nearest in embedding space. Auditability means the recall path can be inspected after the fact, which is what makes it usable in regulated settings where you have to explain why an agent said what it said. The licensing posture is unusually clean for an open-core product: every tier ships the full Apache-2.0 library with all providers and no gated features, and the paid tiers sell hosting, SLAs and compliance help rather than feature unlocks. Current release is 1.5.0, on Python 3.10 and later.

Ideal use cases:

  • Teams or individuals who need local-first by default — sqlite plus faiss, no services to operate
  • Teams or individuals who need importance-scored memory rather than similarity retrieval alone
  • Teams or individuals who need auditable recall path for regulated and high-stakes deployments
  • Teams or individuals who need air-gap capable out of the box
  • Anyone focused on open-source workflows
  • Anyone focused on agent-memory workflows
Try widemem

🤖 Other AI Agent Infrastructure Tools to Consider

BaseMouse and widemem aren't the only options. Here are other popular tools in the same space:

🏷️

Is one of these your tool?

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Frequently Asked Questions

Is BaseMouse better than widemem?

It depends on your needs. BaseMouse offers 8 key features including Single remote MCP server at one endpoint for every registered tool and Shared read/write memory across Claude Code, Cursor, Codex, and Grok, while widemem provides 6 features including Local-first by default — SQLite plus FAISS, no services to operate and Importance-scored memory rather than similarity retrieval alone. BaseMouse uses a freemium model with a free tier, while widemem is open-source with free access available. Choose based on which features and pricing model align with your requirements.

Is BaseMouse cheaper than widemem?

widemem doesn't have standard paid plans, while BaseMouse starts at Open core: the import-and-serve engine is free and MIT-licensed, self-hostable with no license key and nothing phoning home. A paid hosted version adds running, billing, and support, billed through Stripe; the hosted plan figures are rendered client-side and are not published in the page source.. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.

Can I use BaseMouse and widemem together?

Yes, many users combine BaseMouse and widemem in their workflow. BaseMouse excels at single remote mcp server at one endpoint for every registered tool, while widemem shines with local-first by default — sqlite plus faiss, no services to operate. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.

What's the main difference between BaseMouse and widemem?

While both are ai agent infrastructure tools, BaseMouse emphasizes single remote mcp server at one endpoint for every registered tool, whereas widemem is known for local-first by default — sqlite plus faiss, no services to operate. The best choice depends on your specific workflow and feature priorities.

Learn More

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