Agentmemory
Why Choose Agentmemory?
If you are burning through credits on long coding sessions, this is actually the solution u need right now. Standard setups get bloated fast, but this keeps token usage down by roughly 95%, meaning you can run way more tool calls without hitting the wall. For devs doing heavy lifting on big projects, that kind of efficiency is a total game changer. What sets it apart though is the memory handling. Usually after a couple thousand observations half your context gets invisible and useless. With this, 100% of your memories stay searchable no matter how deep you go. U never lose track of why a function was written six months ago which saves hours of digging. Its totally open source so you got full control over the stack. One caveat tho, its integratin isnt as seamless as just clicking a button in the IDE and it targets specific agents like Hermes or Codex mostly. So if you want plug-and-play simplicity it might feel a bit clunky at first.
You can now give Hermes, Claude Code, and Codex infinite memory. Agentmemory is trending on GitHub with 5,000+ Stars. CLAUDE md dumps 22,000+ tokens into context at 240 observations agentmemory: 1,900 tokens. same observations. 92% less. At 1,000 observations, 80% of your built-in memories become invisible. agentmemory keeps 100% searchable. benchmarked on 240 real coding sessions → Up to 95% fewer tokens per session → 200x more tool calls before hitting context limits → 100% open source
Agentmemory Introduction
What is Agentmemory?
Agentmemory is basically a dev tool that gives ai coding agents like Claude or Hermes an infinite memory bank. Its mainly for developers tired of losing context when prompts get too long, keeping everything searchable instead of just dumping garbage into the chat. You can hook it up to Hermes, Codex or whatever else and stop wasting tokens on dead weight. When you check the math, it slashes token usage by like 90% compared to normal methods. You know how regular models choke after a few thousand tokens? This one handles way more before crashing or getting confused. Its totally open source too, which means you can poke around the code if you wanna tweak it yourself without needing permission. Bottom line if your team uses agents for heavy lifting, this saves a ton of resources. It makes sure 100% of memories stay visible even when things get huge. Real world tests show it works way better than the built-in stuff most people are stuck using right now.
How to use Agentmemory?
To get started, you'll wanna grab the repo off GitHub and drop it into yer local workspace. Just clone the thing and run the instal command in yer terminal, though you might wanna double check if you have the right python or node versions before kicking things off. Its super lightweight so dont expect a massive setup wizard, mostly just deps you gotta satisfy before it actually runs. Once it's running, you plug it into whatever coding agent ur using, like Claude or Hermes. You tweak the config file to point to the memory service instead of dumping everything into context manually. Its kinda seamless after that, just start working on projects and the agent starts storing context efficiently without choking on token limits as much. For the first real win, try opening a big project folder and letting it index the files. Youll notice way fewer tokens getting burned compared to standard dumps. If stuff gets weird, check the logs locally cause debugging is easier when you control the memory layer directly. Works great once hooked up properly even if u skip docs sometimes.
Why Choose Agentmemory?
If you are burning through credits on long coding sessions, this is actually the solution u need right now. Standard setups get bloated fast, but this keeps token usage down by roughly 95%, meaning you can run way more tool calls without hitting the wall. For devs doing heavy lifting on big projects, that kind of efficiency is a total game changer. What sets it apart though is the memory handling. Usually after a couple thousand observations half your context gets invisible and useless. With this, 100% of your memories stay searchable no matter how deep you go. U never lose track of why a function was written six months ago which saves hours of digging. Its totally open source so you got full control over the stack. One caveat tho, its integratin isnt as seamless as just clicking a button in the IDE and it targets specific agents like Hermes or Codex mostly. So if you want plug-and-play simplicity it might feel a bit clunky at first.