Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Durable, revision-pinned memory storage and retrieval for AI conversations.
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Pick the AI app you use, then copy the settings.
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Works in Claude on the web, desktop and mobile:
https://mempersist.codifiedtech.id/mcpRun this in your terminal
claude mcp add --transport http mempersist https://mempersist.codifiedtech.id/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"mempersist": {
"url": "https://mempersist.codifiedtech.id/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"mempersist": {
"type": "http",
"url": "https://mempersist.codifiedtech.id/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://mempersist.codifiedtech.id/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
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We have not read this server’s tool list yet; we check endpoints in rotation.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account ravhirizaldi, which owns the repo
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It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 39 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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Long-term memory for AI conversations, running entirely on Cloudflare. Original ChatGPT exports and normalized conversation graphs live in R2, a D1 catalog makes them queryable, lexical and semantic indexes stay disposable, and MCP exposes compact retrieval plus intentional writes.
| MCP endpoint | https://mempersist.codifiedtech.id/mcp |
| Registry | io.github.ravhirizaldi/mempersist — version 1.0.1 |
| Runtime | Workers, D1, R2, Queues, Workers AI (BGE-M3), Vectorize, OAuth KV |
| Protocol | MCP v2 over stateless Streamable HTTP, OAuth 2.1 with PKCE S256 |
| Scope | Single-operator V1, one Worker, one TypeScript package |
What it does. Preserves every uploaded ChatGPT export byte-for-byte, normalizes branches and node metadata into revision-pinned canonical JSONL, indexes derived FTS and vector data, and answers search, context, and batch reads with deterministic IDs. Writes are intentional, revision-checked, and durable before indexing is queued.
What it refuses to do. It does not intercept ChatGPT traffic, extract replacement "facts", summarize with a model, or treat any index as canonical. No billing, organizations, or speculative multi-tenancy; no Durable Objects, Workflows, cron triggers, or containers. Deleting every chunk, FTS row, and vector does not delete memory. "Unlimited" means no application-level message quota — Cloudflare limits and billing still apply.
flowchart TD
IMP["ChatGPT data export (conversations.json)"] --> V WRITE["MCP writes from any client"] --> V V["Validation and stable IDs"] --> R2[("R2 canonical archive raw import + immutable revisions")] R2 --> D1[("D1 catalog imports, revisions, graph, R2 pointers")] D1 --> Q["Cloudflare Queues import and index jobs"] Q --> FTS[("D1 FTS5 lexical chunks")] Q --> AI["Workers AI BGE-M3"] --> VEC[("Vectorize embeddings")] FTS --> SEARCH["Normalized hybrid search plus recent-canonical fallback"] VEC --> SEARCH SEARCH --> OUT["HTTP API and OAuth-protected MCP"] R2 --> EXPORT["Lossless export and recovery"]
Two ingestion paths, and they stay independent: the ChatGPT data export parser accepts the native conversations.json format only, while writes arrive through MCP from whichever client the caller uses. Both converge on the same canonical revision model, so a memory created by a tool call and one imported from an export are read, pinned, and restored identically.
R2 is the source of truth. A canonical write completes before its index job is queued, and an indexing failure never reports that durable memory was lost. Rebuilds read R2, so an export never needs to be uploaded twice. Full detail in ARCHITECTURE.md and docs/storage-and-indexing.md.
yarn install
cp .dev.vars.example .dev.vars # set a long random MEMORY_API_TOKEN yarn types:bindings yarn db:migrate:local yarn dev
Requires WSL2/Linux, Node.js 22+, Yarn 1.22, and Wrangler 4.x authenticated with yarn wrangler whoami. Use Yarn only. Local D1, R2, KV, and Queues are simulated; Workers AI and Vectorize point at real remote bindings in the main configuration, while unit and integration tests never call remote AI.
MemPersist is a standard remote MCP server: stateless Streamable HTTP at https://mempersist.codifiedtech.id/mcp, OAuth 2.1 authorization code with PKCE S256, scope memory. Nothing in the endpoint is client-specific — the same handshake, tool contracts, and server instructions serve every caller. Point a client at the URL and it works:
| Client | How to add it |
|---|---|
| Claude Code | claude mcp add --transport http mempersist https://mempersist.codifiedtech.id/mcp, then finish the email prompt |
| Codex CLI, ChatGPT desktop, IDE extension | ~/.codex/config.toml (or project .codex/config.toml), then codex mcp login mempersist |
| Cursor, Claude Desktop, VS Code, Zed | add the URL as a remote (HTTP) MCP server in the client's MCP settings; the client starts the OAuth flow |
| ChatGPT | Developer mode, then add the URL as a custom MCP app |
| MCP Inspector, custom SDK clients | npx @modelcontextprotocol/inspector, or the official SDK client; use the URL and either OAuth or the developer token |
| stdio-only clients | keep the server remote and bridge stdio to HTTP with an OAuth-capable proxy; MemPersist itself never needs npx |
Codex configuration:
[mcp_servers.mempersist]
type = "remote" url = "https://mempersist.codifiedtech.id/mcp"
codex mcp login mempersist to authorize
The client discovers OAuth from the 401 challenge, opens the consent page, and stores the issued access and refresh tokens. The consent page takes an email and sends a single-use, 15-minute magic link through the EMAIL binding; the connection completes only after that link is opened, and an existing email reconnects to its archive. The single scope is memory, and the sender address is configuration (AUTH_EMAIL_FROM, LEGACY_AUTH_EMAIL_FROM), not part of the API contract. Never paste MEMORY_API_TOKEN into a connector.
Already-configured connections keep working across upgrades without re-authorization; the legacy hostname stays supported, and moving one client to the primary hostname costs exactly one new authorization.
Scripts, the CLI, and non-interactive automation may send Authorization: Bearer instead of OAuth, which always maps to the owner archive. Every account may own multiple namespaces; the same namespace name in two accounts is separate data, and a supplied namespace is honored only when the caller owns it.
The MCP audience is deployment configuration, so point a development server at itself:
yarn dev --local --port 8787 --local-protocol https \
--var MCP_ORIGIN_OVERRIDE:https://127.0.0.1:8787
Discovery, consent, and token audiences then use https://127.0.0.1:8787, and both the .dev.vars developer token and the full OAuth flow work. Local send_email writes each magic link to .wrangler/tmp/email/ /email-text/. See docs/development.md.
24 tools, each carrying a human-readable title and read-only or destructive annotations. Retrieve first, then expand only what you selected.
| Tool | Title | Notes |
|---|---|---|
memory_search | Search memories | Hybrid search, 1–20 references; filters and opaque cursor pagination |
memory_get_context | Get memory context | Canonical messages around one result chunk, up to 10 each way |
memory_get_conversation | Get conversation | Page one conversation's active timeline or full graph |
memory_get_messages | Get messages | Exact source-node or optional keyed lookup, revision-pinned, ordered batch with opaque cursor and byte budget |
memory_get_conversations | Get conversations | Revision-pinned batch read of 1–20 conversations, cursor-paged |
memory_list_conversations | List conversations | Metadata and tags only, no bodies |
memory_list_revisions | List revisions | Immutable revision history, newest first |
memory_resolve_conversations | Resolve conversations | Exact-title lookup, no semantic search |
memory_list_namespaces | List namespaces | Owned namespaces with conversation counts |
memory_stats | Get memory statistics | Per-namespace counts and indexing health |
memory_import_status | Get import status | Import progress, duplicate, or failure |
memory_get_capabilities | Get capabilities | The deployed contract: versions, limits, per-tool bounds, and message_keys / atomic_multi_conversation_commit feature flags |
memory_get_messages accepts 1–100 ordered selectors. Each selector names a conversation_id, optionally pins a revision_id, and uses exactly one of source_node_id (up to 200 characters) or the forward-compatible message_key (1–128 lowercase ASCII letters, digits, ., _, /, or -, starting and ending with a letter or digit). Omitted revisions pin each conversation's current head before any canonical R2 body is loaded; canonical loads are deduplicated by unique pinned revision, while duplicate selectors retain duplicate ordered results. The read-only lookup does not use FTS or Vectorize. Missing, foreign, deleted, or unknown conversations, revisions, nodes, and keys share the same bounded NOT_FOUND result. Duplicate canonical message keys return a bounded canonical-storage error and are never resolved by choosing one. Whole messages are admitted within the 32 KiB default, 4 KiB minimum, and 48 KiB maximum serialized budgets; an oversized message is not truncated and returns only bounded identity/byte diagnostics. Continuations use an opaque, HMAC-signed, tenant-bound cursor that preserves selector order and revision pins.
The optional message_key selector reads keyed fields written by memory_upsert_messages (and any canonical data that carries them). memory_upsert_messages is the stable-key writer for logical records; its contract is documented in the Write section below.
| Tool | Title | Notes |
|---|---|---|
memory_build_context | Build memory context | Deterministic, revision-pinned pack from 1–20 required conversations, optional hybrid evidence, explicit token and byte budgets |
Each write returns a bounded durable receipt with separate indexing and verification status, and accepts verify: true to reload t
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