Echo

A local MCP for Claude Code, Codex & Cursor.
Every session you close becomes memory your agent can pull.
Start every session warm. The baggage stays behind.

[Echo @IditorTeam]

Echo is a local MCP for Claude Code, Codex, and Cursor:
- Turns your past sessions into memory your agent can pull anytime

Same task, with memory: 1.51M → 0.32M cost
Paste this to your terminal ->

npm i -g @echomem/mcp@latest && echomem-mcp init

[Echo @IditorTeam]

@Simonsterrific The job is not going away. it is getting promoted into the layer that decides what the agent may touch, and that layer has no demo, because demos run with permissions nobody would grant in production.

Worth the read.

[Echo @IditorTeam]

@Simonsterrific The sharpest thread here isn't mods, it's the unload problem. Plugin authors shouldn't have to remember to clean up. Same demand on memory: a system shouldn't have to remember to abstain. Reliability has to be structural, not author discipline.

[Echo @IditorTeam]

System one could be a really useful piece for AI Agent Memory or Context Management.

[Simon Zhang @Simonsterrific]

Everyone is asking whether Jev becomes the next agent route. That is the wrong question. Its real signal is that the model gets demoted from driver to a typed function, and "agent" quietly dissolves into infrastructure. https://t.co/jZmxCe6PDW

[Echo @IditorTeam]

Spot on. Increasing token capacity without context engineering just gives the agent a bigger room to lose things in.

The 3-state memory architecture is essential for any real-world AI application—especially when maintaining long-term continuity matters.

[Divyam @talwar_divyam]

A larger context window solves overflow.

It does not solve attention or lossy compaction.

The durable fix is a three-state memory architecture that preserves decisions outside the chat. https://t.co/TSef0jWZr7

[Echo @IditorTeam]

Body + soul is the right framing. Most of the market is optimizing runtime latency; we're optimizing memory continuity across sessions at Echo. This essay explains why the second problem is harder: https://t.co/eWx4q7nOLc

[Simon Zhang @Simonsterrific]

Runtime is the body. Memory is the soul. After Harness, the agent race is about building both—across cloud, local, and every sandbox. https://t.co/TPUWpQ6VOk

[Simon Zhang @Simonsterrific]

Runtime is the body. Memory is the soul. After Harness, the agent race is about building both—across cloud, local, and every sandbox. https://t.co/TPUWpQ6VOk

[Echo @IditorTeam]

@Simonsterrific The Verifier's Law angle is underrated. If capability ∝ verifiability, then local agents touching email / bank / files are structurally stuck — there's no checker.

Seen any pattern where a verifier-in-the-loop actually works outside coding?

[Simon Zhang @Simonsterrific]

Everyone’s asking when agents will get smarter. The real question is: when will we trust them enough to stop watching?

On long-horizon reliability, context rot, and why the next battlefield isn’t intelligence — it’s trust. https://t.co/2RzKWMIODH

[kobe @kobe_acc]

I still use OpenClaw daily🦞2026 will be marked as the year of Agent. Here is why:
1. Nov 2025 — launched.
2. Jan 30, 2026 — relaunched. 100K GitHub stars in 48 hours, fastest in history.
3. 60 days — passed React's 10-year record. Most-starred repo ever: 373K.
4. Apr 4, 2026 — Anthropic blocked third-party subscription tokens. No one has talked about it since.

What the world changed by 🦞:

5. GitHub commits: 83M/month → 1.2B/month. ×14 more!
6. PRs opened by agents: 4M/month → 17M/month.
7. Codex weekly users: 600K → 8M.
8. Claude Code revenue: $0 → $2.5B run-rate.
9. Chinese models: 2% → 45% of OpenRouter tokens.
10. Big-4 AI capex: $410B → $725B.

Before OpenClaw, software was written by developers.
After, by everyone.

[Echo @IditorTeam]

@bboczeng @kobe_acc 求关注

[kobe @kobe_acc]

For fellow Codex/CC power builders:
A $15 toggle workflow that’s ~70% keyboard/mouse free—less typing, less clicking, more talking and building.
Spoiler alert: this video had no script. I just hit record and rambled

Everything you need to start is here:
https://t.co/bLodnaZBtr

[Echo @IditorTeam]

And we build the memory layer!
#harness #container #memory

[Simon Zhang @Simonsterrific]

https://t.co/UbkCafXgzd

[Echo @IditorTeam]

EchoMem achieved 95.8% accuracy on LongMemEval (with Gemini 3.1 Pro). But the real win? Our ability to correctly abstain when the memory doesn’t support the answer.

Read the full performance report: https://t.co/fn13ZpMA0y

#AI #LLM #MemoryInfra #EchoMem #LongMemEval

[Echo @IditorTeam]

Yeah! Echo

The Echo family is live:

• EchoMemory Chrome Plugin
• EchoMemory OpenClaw Plugin
• EchoChat iOS App
• EchoMemory MCP Server

A true Network of Memory.

Capture what matters. Connect deeply. Leave kindness.

👉 https://t.co/bfoFhKe5IM

#EchoMemory #EchoChat

[Echo @IditorTeam]

Full benchmark breakdown: Gemma 4 vs Qwen3.5

MMLU-Pro, MMMU-Pro, LiveCodeBench, TAU2, MathVision, MedXpertQA… all in one view.

TL;DR:

- Qwen leads at the frontier
- Gemma is competitive in practical tiers

But benchmarks miss one thing:
cross-tool memory is still unsolved

[Echo @IditorTeam]

Memory poisoning is now OWASP's #1 agentic risk.

The next generation of agent memory isn't about:
❌ Bigger context windows
❌ More storage
❌ Faster embeddings

It's about:
✅ Governing what gets admitted
✅ Mathematical validation of importance
✅ Immutable audit trails

[Echo @IditorTeam]

🧵 I analyzed 13 memory plugins competing to replace OpenClaw's broken MEMORY.md

The default sliding-window truncation = "agent amnesia"
→ forgotten parameters
→ spiraling token costs
→ failed long-horizon tasks

6 architecture types.

Here's what I found ↓

[Echo @IditorTeam]

The cost of "agent amnesia" is brutal:

OpenClaw's default = reload entire MEMORY.md every turn
→ Hundreds of thousands of redundant tokens per session