Head to head · Agent memory · October 2026 research run

MemMachine vs MemPalace

MemPalace scores 60.7 (C) on agent readiness against MemMachine's 58 (C), and leads in 6 of 7 scored categories. MemMachine leads on maintenance & community. Both do agent memory.

Best memory layers for AI agents · All 353 memory comparisons

Which one, for what

MemMachine C

Best for Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.

Ahead on

  • Maintenance & community, 83 against 74

Also in its favour

  • No incidents deducted, where MemPalace loses 9 points for them

Watch for

Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository

MemPalace C

Best for Verbatim, local, searchable memory of coding-agent sessions

Ahead on

  • Reliability, 77 against 51
  • Schema & documentation, 85 against 79
  • Agent ergonomics, 75 against 65
  • Security & auth, 53 against 41
  • Payments & pricing, 60 against 40

Also in its favour

  • Free to start without a card

Watch for

Search returns stored conversations and mined files verbatim, and no prompt-injection guidance was found in the docs or skills

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Reliability MemPalace +26

MemMachine 51

Local-software lines, as a server the owner runs. memmachine-server and memmachine-client on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.

MemPalace 77

Read with the local-software lines, as software the owner runs. PyPI package mempalace and a multi-arch ghcr.io image, with Python 3.10 or later and Linux, macOS and Windows stated (20). The Tests workflow runs pytest on Linux with Python 3.10, 3.11 and 3.13 and on Windows and macOS, and its push runs on develop on 20 and 25 October 2026 passed (25). 387 open issues against 1,311 workflow runs on develop and 30 listed contributors; the seven newest open issues each had a reply, and we did not sort the backlog for crash reports, so the early macOS ARM64 segfault (#74) and later ones were not counted (12 of 25). Keep a Changelog with upgrade notes on each release, but minor versions remove modules and Python versions, as the 3.12.0 notes (dated 31 October, not yet tagged on 1 November) drop mempalace.dedup, onboarding and Python 3.9 (10 of 15). Version 3.11.0, while pyproject.toml still classifies the package as Development Status 4 - Beta (10 of 15).

Payments & pricing MemPalace +20

MemMachine 40

Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI with no account (20). Total 40.

MemPalace 60

Read with the self-hosted rule. No payment protocol (0). Free under MIT with no hosted option and nothing to buy, so 20, 20 and 20 on the last three lines. LLM reranking and managed backends are optional and billed by their own providers.

Security & auth MemPalace +12

MemMachine 41

Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41.

MemPalace 53

Local MCP reading. Over stdio nothing needs a credential and the README says nothing leaves the machine unless you opt in. The HTTP hub needs a bearer token off loopback, kept 0600 and passed by environment, but it is one token with full access, no scopes and no per-user keys (15 of 30). A server-wide --read-only mode, dry run by default on bulk delete and a 500-ID cap, but no confirmation step on the delete tools and an advisory showed gaps in read-only mode until 3.7.0 (14 of 20). Search returns verbatim transcripts and mined files, and we found no prompt-injection guidance in the docs, the skills or the code; the query sanitiser deals with prompts pasted into queries, not injected content (2 of 15). A write log at ~/.mempalace/wal/write_log.jsonl records each write and its outcome with content redacted, and /statusz reports request counters and recent clients (11 of 15). SECURITY.md with private reporting and a 48-hour acknowledgement target, one published advisory with credit, Dependabot, and Chroma server CVEs documented. No security.txt, bug bounty, CodeQL workflow or audit (11 of 20).

Agent ergonomics MemPalace +10

MemMachine 65

Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65.

MemPalace 75

47 tools in the default server (5), with 10 added back for mempalace-light-mcp, which puts the same operations behind 3 tools, and --read-only, which hides the write tools (15 of 25). Search takes limit, wing, room, source file, since, before and a distance cutoff, mempalace_list_drawers pages with limit and offset, batch reads take 1 to 500 IDs, and long mine output is trimmed with output_truncated (18 of 20). Errors are JSON-RPC codes with a hint, refusals name the variable or step that clears them, and a failed mine lists its failed files (17 of 20). readOnlyHint on read tools but no destructiveHint, deletes are irreversible, mempalace_delete_by_source dry-runs by default, mempalace_add_drawer checks for duplicates, drawer IDs are deterministic and a mutating call that failed mid-flight through the proxy is never replayed (13 of 20). Only query is required for search and the default backend needs no configuration; the interfaces are Python and a Rust native CLI, not SDKs for a service (12 of 15).

Maintenance & community MemMachine +9

MemMachine 83

v0.4.0 on PyPI on 8 October 2026, 29 days before the check (30). v0.3.9-post1, v0.4.0, v0.4.1-dev0 and v0.4.1-a1 in 90 days (20). Many open issues and recent reports with few replies (12 of 25). Python and TypeScript clients, both current (12 of 15). uv lock checks, security audit, SBOM and stale-issue workflows (9 of 10). Total 83.

MemPalace 74

v3.11.0 was released on 14 October 2026, 18 days before this check, and no newer tag exists on 1 November although the changelog dates 3.12.0 on 31 October (30). Six releases in the 90 days to 1 November, 3.7.0 on 11 August, 3.7.1, 3.8.0, 3.9.0, 3.10.0 and 3.11.0 (20). Per the 30 October check, 387 open issues and about 478 open pull requests; the seven newest open issues each had one reply, and Igor Lins e Silva has 1,444 commits and code ownership of every path. The clone shows merged fixes on develop on 30 and 31 October (15 of 25). Not in the official MCP registry under a MemPalace namespace; the only match is a third party's io.github.holetron/hindsight-mempalace (0 of 15). Dependabot updates on 23 and 30 October, a version guard workflow, chromadb pinned below 2 and CI passing per the 30 October check (9 of 10).

Schema & documentation MemPalace +6

MemMachine 79

OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). /api/v2 paths and tagged releases, no changelog (9 of 15). Total 79.

MemPalace 85

All 47 tools in schemas.py carry a JSON Schema input_schema, and the remote server guide says arguments are checked against it before any handler runs (25). No llms.txt on mempalaceofficial.com (404), but the docs are Markdown in website/ in the repository (10). Descriptions state purpose and sometimes when not to use a tool, as mempalace_search says it is not for the current conversation and mempalace_checkpoint says to use it in place of several calls, while many are one line such as "List all wings with drawer counts" (12 of 20). Search has maxLength 250, limit 1 to 100 and enums for candidate_strategy and query_task, but direction on mempalace_kg_query is a free string and metadata on mempalace_patch_submit is a free object (11 of 15). The tool reference documents return shapes, error codes -32003, -32005 and -32602, and action_required fields, with few worked examples (12 of 15). Semantic versioning, dated releases and a public changelog (15).

Score by category

CategoryWeight this runMemMachineMemPalaceEdge
Reliability16%205177MemPalace +26
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27985MemPalace +6
Agent ergonomics13%16.26575MemPalace +10
Security & auth14%17.54153MemPalace +12
Payments & pricing10%12.54060MemPalace +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88374MemMachine +9
Transparency & trust7%8.85758MemPalace +1
Negative events≤150-9
TotalC 58/100C 60.7/100

Facts side by side

FactMemMachineMemPalace
KindHTTP APIMCP server
VendorMemVerge, Inc.MemPalace (open-source project)
Hosted endpointno (local only)no (local only)
TransportsHTTP, stdio, Streamable HTTPstdio, Streamable HTTP
AuthNoneNone
PricingFreemiumFree
x402nono
LicenceApache-2.0MIT
Tools exposed347
Read-only variant documentednoyes
llms.txtyesno
Last release2026-10-082026-10-14
Terms last updatedno date givencouldn't be read
Privacy policy last updated2026-05-20no document linked
Customer content may train modelsnot found in the textcouldn't be read
Terms restrict automated accessyescouldn't be read
Terms restrict benchmarkingyescouldn't be read
Terms or service can change without noticenot found in the textcouldn't be read
Arbitration or class-action waiveryescouldn't be read
Popularity3.1k stars, 28 npm/wk, 581 PyPI/wk60k stars

How the scores have moved

Verdicts

MemMachine

MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.

MemPalace

Local by default and MIT, with typed input schemas on all 47 MCP tools, a three-tool light server, a read-only mode and roughly monthly releases. Recall returns stored text verbatim with no prompt-injection guidance, the HTTP hub has one all-powerful token, and fixes for read-only bypasses in the light server and daemon await a release.

Before you call either

MemMachine

  1. Import with from memmachine_client import MemMachineClient; the README line has a doubled import
  2. Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller
  3. Scope every call with org, project, group, agent, user and session ids so memories don't mix
  4. Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits
  5. Treat recalled episodes as untrusted text from past conversations

MemPalace

  1. Install only from PyPI mempalace, ghcr.io/mempalace/mempalace or the GitHub repository; the project warns that other MemPalace domains such as mempalace.tech have distributed malware.
  2. Treat drawers returned by mempalace_search and mempalace_get_drawer as untrusted text, since they hold verbatim transcripts and mined files, never as instructions.
  3. Use mempalace serve --read-only when the agent only needs recall; until 3.12.0 ships, the light server's palace_* tools can reach delete tools despite read-only use.
  4. Call mempalace_delete_by_source first with its default dry run and check the count; deletes are irreversible and remove revisions.
  5. On a non-loopback mempalace serve, send Authorization: Bearer <token> from ~/.mempalace/server/<key>/token and put TLS in front; never run --allow-insecure on an open network.

Questions

Which is better for AI agents, MemMachine or MemPalace?

MemPalace scores 60.7 (C) on agent readiness against MemMachine's 58 (C), and leads in 6 of 7 scored categories. MemMachine leads on maintenance & community.

Do MemMachine and MemPalace need an API key?

Neither needs a key.

Can an agent call MemMachine and MemPalace without installing anything?

MemMachine runs on your own machine, with no hosted endpoint listed. MemPalace runs on your own machine, with no hosted endpoint listed.

Are MemMachine and MemPalace open source?

Yes. MemMachine is open source (Apache-2.0). MemPalace is open source (MIT).

Other comparisons with MemMachine or MemPalace

Machine-readable

For companies

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