MCP-Recall vs AI Eyes
Comprehensive feature analysis, ratings breakdown, platform compatibility, and community review comparison.
MCP-Recall
Keeps MCP tools' output from filling your context
Detailed Feature Comparison Matrix
Compare Other Tools| Dimension | AI Eyes | |
|---|---|---|
| Primary Category | Open Source | Open Source |
| Community Rating | No ratings(0 reviews) | No ratings(0 reviews) |
| Community Upvotes | 6 votes | 63 votes |
| Supported Platforms | Web | Web |
| Tags & Focus | #Artificial Intelligence#Developer Tools#Open Source#GitHub | #Developer Tools#Open Source#Privacy#OpenAI Day |
| Maker / Company | Independent Developer | Independent Developer |
| Platform Verification | Community Listing | Community Listing |
About MCP-Recall
MCP-Recall is an open-source developer tool designed to solve context window bloat in heavy Model Context Protocol (MCP) workflows. By automatically compressing tool outputs—reducing payloads like 94 KB down to just 3.5 KB (a ~96% reduction)—MCP-Recall prevents tool responses from overflowing your LLM session context.
Instead of discarding full response data, MCP-Recall persists the complete, uncompressed tool outputs into an SQLite database for subsequent retrieval when needed. This architecture enables developers and AI agents to handle up to 30x more tool calls per session during resource-intensive tasks. Created by Jonathan Tomek, the project is open-source and accessible via GitHub and NPM.
Pros of MCP-Recall
- Compresses tool output sizes by up to 96% (e.g., 94 KB down to 3.5 KB)
- Stores raw, uncompressed response data in SQLite for future retrieval
- Enables up to 30x more tool calls per session for heavy MCP workloads
- Open-source developer tool available on GitHub and NPM
Cons of MCP-Recall
- Designed specifically for Model Context Protocol (MCP) environments
- Requires managing database retrieval when full output details are needed
- Currently lacks extensive community reviews or user ratings
Frequently Asked Questions
What is MCP-Recall?
MCP-Recall is an open-source tool for developers working with the Model Context Protocol (MCP). It compresses tool outputs to save context window space and persists full response data to SQLite for retrieval.
How does MCP-Recall save context space?
It compresses large output payloads—achieving reductions of around 96% (such as scaling 94 KB down to 3.5 KB)—allowing your session context to stay lean while saving full outputs in a local database.
How many tool calls can I run using MCP-Recall?
By dramatically reducing context consumption per response, MCP-Recall allows heavy MCP workloads to execute up to 30x more tool calls within a single session.
Where can I find and install MCP-Recall?
MCP-Recall is available as an open-source repository on GitHub and can be installed via NPM.
About AI Eyes
AI Eyes is a permission-first co-presence prototype designed for AI companions. Created by developer Deen Storkey, this open-source tool establishes a privacy-focused, local-first foundation for managing what your digital companions can see and hear.
With its initial v0.1 release, AI Eyes allows users to choose a specific screen or window to capture and gives granular, separate controls for screen, system audio, and microphone inputs. The interface makes it easy to invite named companions and ensures transparency by always displaying when sensing is active. Users can pause or end sessions at any time; ending a session immediately stops all media tracks and resets the session completely.
Built using Codex and GPT-5.6, this prototype is focused entirely on local-first permission, presence, and session-control. Please note that in this foundational stage, no external AI provider or semantic understanding has been connected yet.
Pros of AI Eyes
- Privacy-focused, local-first permission architecture
- Separate, granular control over screen, system audio, and microphone capture
- Clear visual indicators showing when active sensing is occurring
- Open-source code base allowing developers to review and build upon the prototype
Cons of AI Eyes
- It is a prototype (v0.1) and does not yet have an active AI provider or semantic understanding connected
- Limited to foundational capture and session-control features at this stage
Frequently Asked Questions
What is AI Eyes?
AI Eyes is an open-source, permission-first co-presence prototype built to manage what AI companions can access. It provides local-first controls over screen sharing, audio, and session state.
Does AI Eyes currently analyze my screen or voice?
No. In the v0.1 release, no AI provider or semantic understanding is connected. The prototype is currently a local-first foundation focused on permission, capture, presence, and session-control.
How do I control my privacy while using AI Eyes?
AI Eyes lets you choose exactly which screen or window to capture and gives you separate toggle controls for your screen, system audio, and microphone. There is also a clear indicator to show when sensing is active, and you can pause or end the session to stop all media tracks instantly.
What technologies were used to build AI Eyes?
The AI Eyes prototype was built using Codex and GPT-5.6.
