Memwright MCP Server
Cut your agent's token burn 21×. Two API calls. Full-context replay re-reads the whole conversation every turn - input tokens that grow O(n²) and a bill that compounds with every session. Attestor retrieves only what's needed: flat ~200 tokens per call, 21× fewer input tokens by turn 100, 100% recall - measured across six models, open and closed. It runs locally over stdio via the published package.
People connecting memory tools to Claude, Cursor, VS Code, or another MCP client. The project is written in Python.
VERIFIED ACTIVE
LAST COMMIT 2026-05-30 · ★ 14 · #106 OF 259 MAINTAINED MEMORY · VERIFIED 2026-08-25
MIT · Python servers · how we verify → /methodology
01 · Install Memwright
Claude Code
claude mcp add bolnet-agent-memory -- uvx memwright Claude Desktop / Cursor / VS Code - add to config
{
"mcpServers": {
"bolnet-agent-memory": {
"command": "uvx",
"args": [
"memwright"
]
}
}
} Same JSON for Cursor. For VS Code, rename the top-level key from `mcpServers` to `servers`.
Using another client? Same JSON, different key
Claude Desktop · mcpServers
Cursor · mcpServers
VS Code · servers
Windsurf · mcpServers
Zed · context_servers
Cline · mcpServers
Roo Code · mcpServers
Continue · mcpServers
LibreChat · mcpServers
Gemini CLI · mcpServers
Codex CLI · mcp_servers
Full setup guides: every client.
02 · Evidence
Security posture
What to check before giving this server access to your agent - from the registry, GitHub, and our own probes. We don't score safety; we show what's verifiable.
runs as local process (stdio) - runs on your machine with your user's permissions
license MIT - declared in the repository
pypi package memwright - check the name against the project README before installing (PyPI has no namespace ownership)
registry namespace io.github.bolnet is GitHub-verified and matches the repo owner
03 · What Memwright can do
Prose above is summarized from the project's README and registry record - no invented capabilities.
Latest releases
v4.1.11 · 2026-05-26
Adds attestor recall --show-tokens: prints the packed token count of the recall payload so per-call recall size is visible (flat regardless of conversation length). Ships alongside the 4.1.10 uncapped budget.
v4.1.10 · 2026-05-26
Reverses the 2048 cap (4.1.9): recall budget set to 1,000,000 (effectively uncapped; still bounded by vector_top_k) so we observe real token usage before tuning. Applied to MCP default, CLI --budget, init config…
v4.1.8 · 2026-05-26
Every Docker container, volume, network, and the compose project is now named attestor_… - so docker ps -a | grep attestor, docker volume ls | grep attestor, and docker network ls | grep attestor list everything…
04 · Who maintains Memwright
memwright is maintained by bolnet. We track 2 MCP servers from bolnet - 2 actively maintained, 28 combined GitHub stars, oldest repo from Mar 2026. Full record: all servers from bolnet.
05 · Facts
- repository
- github.com/bolnet/agent-memory
- category
- memory - ranked #106 of 259 actively-maintained memory servers as of 2026-08-25.
- registry
- io.github.bolnet/memwright (active, first published 2026-03-07 · 2 versions)
- packages
- pypi:memwright
06 · Memwright FAQ
What is Memwright?
Cut your agent's token burn 21×. Two API calls. Full-context replay re-reads the whole conversation every turn - input tokens that grow O(n²) and a bill that compounds with every session. Attestor retrieves only what's needed: flat ~200 tokens per call, 21× fewer input tokens by turn 100, 100% recall - measured across six models, open and closed. It runs locally over stdio via the published package.
Is Memwright still maintained?
Yes - as of 2026-08-25, its last commit was 2026-05-30. We re-verify nightly.
How do I install Memwright?
Run `uvx memwright`. You can also paste the ready-made client config above.
Does Memwright run locally?
Yes - it's a stdio server: it runs on your machine (via uvx) with your user's permissions. Your data stays local unless the server itself calls external APIs.
07 · Alternatives to Memwright
Alternatives to Memwright
Maintained memory servers if Memwright isn't the fit.
- Codebase Memory Codebase knowledge graph for AI agents - 159 languages, sub-ms queries, 99% fewer tokens. ★ 40,198 · 2026-08-23
- Tradememory Protocol MCP memory for AI trading agents. Store trades, recall similar setups, track strategy performance. ★ 1,412 · 2026-08-11
- Superlog Open-source agent that observes and fixes your application. Query logs, traces, metrics, incidents. ★ 1,394 · 2026-08-23
- Persome Local-first personal memory and model server for trusted MCP agents on macOS. ★ 1,314 · 2026-08-21
- Neo4j Memory MCP Neo4j Knowledge Graph Memory Server ★ 979 · 2026-04-10
- Projectmem Local-first memory + judgment layer for AI coding agents - warns before repeating failed fixes. ★ 750 · 2026-08-06
Pairs well with
Servers that cover what Memwright doesn't - only shown when the pairing reason fits the companion.
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