Agentmemory vs Temporal AI

Side-by-side comparison of features, pricing, and ratings

Live tool data as of 2026-07-17
Reviewed by our team on
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At a glance

DimensionAgentmemoryTemporal AI
Pricingfreefreemium · from Essentials $100/mo
Best forDevelopers using Claude Code who need persistent memory across sessions, Teams working on large codebases where agents lose contextTeams building AI agents that must survive crashes, retries, and long-running loops, Orchestrating multi-step microservices with automatic retries and compensating transactions
Standout features12 auto-capture hooks for agent tool calls, prompts, stops · Triple-stream retrieval: BM25 + vector + knowledge graph · On-device reranker achieving 95.2% R@5 recall on LongMemEval-SDurable Execution with automatic state capture at every step · Workflows with persistence and recovery from failures · Activities with automatic retries and timeouts
Viability score87/10095/100
APIYesYes

Agentmemory is the stronger pick for developers using claude code who need persistent memory across sessions; Temporal AI fits better for teams building ai agents that must survive crashes, retries, and long-running loops.

Built from live tool data, last verified 2026-07-17.

Agentmemory
Agentmemory

Open-source persistent memory runtime for AI coding agents with 95.2% recall

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Temporal AI
Temporal AI

Durable execution platform for building reliable AI agents and workflows.

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Pricing
Free
Freemium
Plans
Free
$100/mo
$500/mo
Contact Sales
Contact Sales
Popularity
1 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
CLIPluginAPI
WebAPICLI
Categories
💻 Code & Development⚙️ Developer Infrastructure
⚙️ Developer Infrastructure
Features
12 auto-capture hooks for agent tool calls, prompts, stops
Triple-stream retrieval: BM25 + vector + knowledge graph
On-device reranker achieving 95.2% R@5 recall on LongMemEval-S
~92% token reduction vs full-context approaches
Hourly consolidation: compress, merge duplicates, decay stale
53 MCP tools for memory operations
128 REST endpoints mirroring MCP surface
Graph extraction and knowledge graph visualization
Mesh federation: peer-to-peer sync over authenticated HTTPS
Markdown Obsidian export with frontmatter tags
OTEL observability with spans and logs (Jaeger, Honeycomb, Tempo)
JSONL session import from Claude Code transcripts
Supports 5 LLM providers (Claude, Anthropic, Gemini, MiniMax, OpenRouter)
Zero external databases: runs on local SQLite/JSON
Real-time viewer on port 3113 and engine console on port 3114
Durable Execution with automatic state capture at every step
Workflows with persistence and recovery from failures
Activities with automatic retries and timeouts
Multiple SDKs: Python, Go, TypeScript, Ruby, C#, Java, PHP, Rust
Human-in-the-Loop via signals and pause/resume
Saga pattern via compensating transactions
Workflow Streams for real-time interactivity (announced Replay 2026)
Serverless Workers (no worker management needed) (announced Replay 2026)
Standalone Activities for independent execution (announced Replay 2026)
Task queues with priority and fairness
External Storage for large payloads
Full visibility UI into execution state and history
Self-hosted open-source or managed Temporal Cloud
Temporal Cloud on Azure (invite-only pre-release)
Custom Roles for granular permissions (pre-release, June 2026)
Integrations
Claude Code
Cursor
GitHub Copilot
Codex CLI
Gemini CLI
Cline
OpenRouter
Anthropic API
Gemini
MiniMax
Obsidian
Jaeger
Honeycomb
Tempo
OpenClaw
OpenAI Agents SDK
Google ADK
Slack
NVIDIA GPU fleet
Salesforce
Twilio
Braintrust
Docker
Kubernetes
Azure

Who should pick which

  • Solo developer using Claude Code
    Pick: Agentmemory

    Agentmemory provides persistent memory across sessions with no setup cost, directly integrating with Claude Code via MCP hooks.

  • Team building reliable AI agents that must survive failures
    Pick: Temporal AI

    Temporal's durable execution and automatic retries ensure agents recover from crashes, with built-in human-in-the-loop and visibility.

  • Open-source enthusiast wanting self-hosted memory runtime
    Pick: Agentmemory

    Agentmemory runs as a single Node.js process with no external deps, fully open-source, and is easy to deploy.

  • Enterprise orchestrating microservices in production
    Pick: Temporal AI

    Temporal supports multiple SDKs, Saga patterns, and integrations with Kubernetes/Azure, plus cloud with custom roles.

  • Researcher comparing memory frameworks
    Pick: Agentmemory

    Agentmemory offers triple-stream retrieval with high recall and open MCP tools, aligning with new Universal Memory Protocol trends.

Frequently Asked Questions

Which is better, Agentmemory or Temporal AI?

The best choice between Agentmemory and Temporal AI depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.

What are the main differences between Agentmemory and Temporal AI?

The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.

Is there a free version of Agentmemory or Temporal AI?

Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.

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Explore each tool further

Agentmemory
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Temporal AI
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