Context7
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제작자가 쓴 설명(영어 원문)
Agent memory that keeps every correction, with history and as-of reads. Runs on your database.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
제작자가 레지스트리에 설치 정보를 올리지 않았어요. 아래 제작자의 README를 확인하세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 Polign 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.24.0)은 7일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Recall gives an agent memory and state that survive the conversation and the process. Memory is what the agent knows: facts a user stated, with every correction kept, so the agent can say what it believes now, what it believed before, and why. State is where the agent is: its progress, its notes to its next instance, and the tool calls it had in flight, so a run that crashes or moves machines resumes from its own records.
Recall is a Go library, a recall binary that serves the same operations as MCP tools and as HTTP, and a Python client. It stores everything in a database you run: polign_db, PostgreSQL, MongoDB or Qdrant. Apache 2.0.
One user over nine months, three homes, three employers, three work emails, six questions, Claude Opus 5.5 extracting, answering and judging for all three systems: Recall 18/18, mem0 18/18, Zep 12/18. Tokens to save one message: Recall 3.0k, mem0 12.7k, Zep 14.7k.
The code to the Recall repository.
pip install polign-recall # the Python client, the recall binary, and the database it runs
brew install polign/tap/recall # the same for Homebrew go install github.com/Polign/recall/cmd/recall@latest # the binary alone; it fetches the database on first use
Then give it to the agent you use:
claude mcp add recall -- recall mcp -write # Claude Code
Add to Cursor · Add to VS Code · any other MCP host: command recall, arguments mcp -write (details).
With nothing configured, memory lives in a local database in ~/.local/share/recall, started on first use and shared by every agent on the machine. No model and no API key are needed to start. To keep memory in a database you already run, see Backends.
Every change is kept. Three commands read the record:
$ recall history "which editor do I use"
user preferred editor believed now: user preferred editor: zed 2026-09-01 10:00 stated, user_stated
$ recall ask -as-of 2026-09-25 "which editor do I use" Believed as of 2026-09-25 00:00: user preferred editor: emacs (since 2026-09-20) replaced: vim (since 2026-09-01)
$ recall diff -from 2026-09-15 -to 2026-10-31 Changed between 2026-09-15 00:00 and 2026-10-31 00:00:
as_of, history and diff say what the agent believed then and when that changed.recall explain shows the message a fact came from, the rule that decided it, and its history.Python 3.10 or later. Save a preference, then correct it:
pip install polign-recall
python - <<'PY' from polign_recall import Client
with Client(local_dir="./recall-data", typed=True) as memory: memory.remember("user", "prefers_editor", "vim") memory.remember("user", "prefers_editor", "neovim") PY
A second process reads the current value, the history, and what was believed before the correction:
python - <<'PY'
from polign_recall import Client
with Client(local_dir="./recall-data", typed=True) as memory: print(memory.recall("user", "prefers_editor")[0].value) # neovim
events = memory.history("user", "prefers_editor") print([e.value for e in events]) # ['vim', 'neovim']
before = memory.recall("user", "prefers_editor", as_of=events[0].observed_at) print(before[0].value) # vim PY
The first client to open ./recall-data starts a local database for it and later clients share it; the memories stay there after the program exits. A bare Client() uses ~/.local/share/recall, the memory every agent on the machine shares. The Python client guide covers the rest: plain-text memory with a model, forgetting, history, and resuming an agent.
A memory is a subject, a predicate and a typed value: user, prefers_editor, neovim. Predicates live in a registry that says what type a value has, whether the predicate holds one value or many, and which predicates it contradicts: dislikes excludes likes, gave_away excludes owns. A single-valued predicate replaces its value on a new statement; a multi-valued one accumulates. Forgetting records a withdrawal; nothing is deleted. Recall ships starter registries for coding, personal assistant, support, sales and voice agents, and you can change a registry later without touching what was already remembered.
You do not have to define predicates. With an open vocabulary the first use of a predicate defines it, and with a model configured the MCP tools take plain text and no predicates appear anywhere:
recall setup -extract-model anthropic:claude-haiku-4-5-20251001
remember("I switched from helix to zed last week")
recall("which editor do I use?") -> "user prefers editor: zed" (before: helix) forget("my editor")
The model decides how each statement is filed. Once filed, replacement follows the predicate's rule, every filing is recorded, and a wrong filing is corrected with one event that every later answer follows. No model reconciles memory on its own: Recall applies the registry's rules, shows what may conflict, and lets the agent confirm the rest, so every correction reads back to the rule or statement that made it. recall mcp -typed serves the typed tools (remember(subject, predicate, value)) instead. The developer reference has the details and the Memory API is the contract.
The second half of Recall, with its own contract, docs/state-api-v1.md. An agent writes down where it is as it works, and a new process resumes from those records instead of from a snapshot:
Resume takes a lease on the agent id, so one process acts for an agent at a time, rebuilds the context within a token budget, and renders it as one briefing for the model:
agent, err := client.Resume(ctx, recall.ResumeRequest{AgentID: "coder-1", TokenBudget: 8000})
if err != nil { return err } defer agent.Release(context.Background())
briefing := agent.Resumed().Briefing // hand this to the model
In Python, an agent remembers a fact and records where it is, the process is killed, and a new process resumes from the records:
import os, signal
from polign_recall import Client
with Client(local_dir="./recall-data", agent=True, typed=True) as client: client.remember("user", "project_constraint", "deploy only on weekdays after 18:00 UTC") with client.resume("coder-1") as agent: agent.update_working_state(goal="Move billing to the v2 API", plan=["find call sites", "migrate them", "run the tests"]) agent.record_turn("user", "Start with the charge endpoint.") agent.milestone("call sites found", progress="12 call sites listed") os.kill(os.getpid(), signal.SIGKILL) # dies here, lease unreleased
import time
from polign_recall import Client
with Client(local_dir="./recall-data", agent=True, typed=True) as client: agent = client.resume("coder-1", token_budget=8000, defer_lease=True) print(agent.context.briefing) # at once: the goal, plan, milestone, turn, and constraint while not agent.acquire(): # False until the dead process's lease expires time.sleep(1) agent.record_turn("assistant", "Picking up at the charge endpoint.")
Without defer_lease=True, resume raises lease_held until the crashed process's lease expires (Python client guide).
The same operations are MCP tools (agent_resume, update_working_state, record_turn, begin_action, ...) and, on recall serve, HTTP routes at POST /v1/agent/ . Over HTTP the server holds the lease between requests: resume returns an epoch and every write carries it, so a stale process cannot write over its successor. The State API is beta; the records it writes are stable (STABILITY.md). The resume example kills an agent mid-task and continues it in a new process.
recall mcp is one agent, one process. recall serve is the same memory and state for many agents over HTTP, each inside the namespace its key names. The server holds the database credentials; agents hold Recall keys.
recall serve -backend polign -url http://polign:23000 -bootstrap-key-file admin.key
recall key create -backend polign -url http://polign:23000 -namespace acme:agent-7 -expires 168h
Each namespace gets its own collection, so nothing a caller sends can reach another namespace's records. POST /mcp is MCP over streamable HTTP; POST /v1/ takes a memory tool's arguments as the body, and POST /v1/agent/ a state tool's. Any stdio MCP client reaches the server through recall connect with RECALL_URL and RECALL_API_KEY set.
On Kubernetes a pod needs no key at all. With recall serve -kubernetes, it posts its projected service account token and gets a short-lived key fixed to its own agent id, which recall connect and the Python client obtain and renew by themselves. The Helm chart is charts/recall in Polign/polign; the agent-sandbox demo runs it on kind.
| local (default) | polign_db | PostgreSQL + pgvector | MongoDB | Qdrant | |
|---|---|---|---|---|---|
RECALL_BACKEND | local | polign | pgvector | mongodb | qdrant |
RECALL_BACKEND_URL | a directory | http://host:23000 | postgres://user:pw@host/db | mongodb://user:pw@host/db | http://host:6333 |
| Memory, history, as-of | yes | yes | yes | yes | yes |
| Keyword search | yes | yes | yes | yes | no |
| Cached reads | yes | yes | yes | yes | no |
| State API (leases) | yes | yes | yes | yes | no |
export RECALL_BACKEND=pgvector RECALL_BACKEND_URL=postgres://user:password@localhost:5432/mydb
recall mcp -write
Three settings name the database for every command: -backend, -url and `-ke
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