Tempreon
ChainMemory
Memori
Mem0
Agentmemory
TheSecondBrain.dev
cognee
VATES.jp
CodeRifts
Bump.sh
StopLight
Spectral
Insomnia CLI
Merge Freeze
Optic
Tempreon is a personal memory layer for your AI tools, connected over MCP. Your knowledge, preferences, and decisions travel across Claude, ChatGPT, Cursor, and any MCP-capable client — captured once, available everywhere. It learns how you actually work instead of just storing what you said.
CodeRifts detects breaking changes in OpenAPI schemas on every pull request. It scores risk across 4 dimensions (revenue impact, blast radius, app compatibility, security), enforces governance policies before merge, and translates technical API changes into business impact — blast radius, affected clients, and estimated cost.
Works with GitHub, GitLab, Bitbucket, and any CI/CD pipeline. Zero config. Free to start.
Key features: - Breaking change detection with risk scoring (0-100) - Policy engine: breaking budgets, freeze windows, approval matrix - Economic impact estimation: cost and engineering effort - Security analysis: auth changes, sensitive field exposure - Auto-changelog and semver suggestions - GitHub App, GitHub Actions, GitLab CI, Bitbucket Pipelines, REST API, CLI
Tempreon
CodeRiftsCodeRifts's answer:
Currently in beta, onboarding early adopters
Tempreon's answer
Tempreon is built for the person, not the app. Most memory products are developer APIs for adding memory to a single product; Tempreon is a memory layer you own that travels with you across every AI tool you use — Claude, ChatGPT, Cursor, anything MCP-capable.
CodeRifts's answer:
CodeRifts is the only API governance tool that combines breaking change detection with risk scoring, policy enforcement, and economic impact estimation — all delivered as a zero-config GitHub App. It does not just tell you what changed, it tells you how dangerous it is, who it affects, and what it will cost to fix.
Tempreon's answer
Tempreon started with a simple observation: AI models keep changing, but the thing that makes them useful to you — your context, your preferences, your judgment — gets rebuilt from scratch inside every tool, and lost every time you move.
We built the layer that fixes that: person-owned memory served over the open Model Context Protocol, so it works across assistants instead of belonging to one. Along the way we open-sourced the pieces that are useful to everyone regardless of whether they use Tempreon — like memhaul, our MIT-licensed CLI for turning ChatGPT and Claude data exports into files you own.
The through-line is custody: the model is temporary, your memory shouldn't be.
CodeRifts's answer:
A field rename broke a POS system across 19 restaurants for a week. The PR passed code review, all tests were green, nobody checked the API schema. CodeRifts was built to catch this class of problem before merge — automatically, on every pull request.
Tempreon's answer
Most alternatives in this space are memory infrastructure for developers building their own AI apps. If you're the person using several AI tools every day, that's not your problem — your problem is re-explaining yourself to each of them and losing everything when you switch.
The choice is really about who the memory is for. Ours is for you.
CodeRifts's answer:
Most tools only diff your OpenAPI specs. CodeRifts goes further: it scores risk across 4 dimensions, enforces governance policies before merge, estimates migration costs in dollars and engineering hours, and works with GitHub, GitLab, Bitbucket, and any CI/CD pipeline. One YAML file replaces review meetings.
Tempreon's answer
Individuals who live in AI tools all day: operators, consultants, founders, sales professionals, and knowledge workers who use more than one assistant and are tired of being a stranger to each of them.
If you've ever pasted the same context into Claude and ChatGPT in the same week — you're the audience.
CodeRifts's answer:
Senior backend engineers, platform engineers, and staff engineers at companies with microservices architectures who need to prevent breaking API changes from reaching production.
Tempreon's answer
The protocol choice is the product decision: build on the open standard, and your memory works everywhere the standard does.
CodeRifts's answer:
Node.js, Express, GitHub Apps API, OpenAPI diff engine, Railway, Cloudflare Pages
ChainMemory - Portable, verifiable memory for AI agents — works across ChatGPT, Claude, Gemini and any MCP client
Bump.sh - Much more than stunning docs. For all your APIs.
Memori - Persistent memory from agent trace, not just conversation
StopLight - Stoplight is an API Design, Development, and Documentation platform that enables consistency, reusability, and quality in your API lifecycle, all with an easy, enjoyable developer experience.
Mem0 - Your private, local memory layer for all AI tools
Spectral - Spectral is an experimental Sinclair ZX Spectrum emulator from the 80s, which has been randomly assembled since the pandemic days. Accuracy and performance are long-term goals, but the primary focus is just having fun with this thing.