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
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
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
| Category | Weight this run | MemMachine | MemPalace | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 51 | 77 | MemPalace +26 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 79 | 85 | MemPalace +6 |
| Agent ergonomics | 13%16.2 | 65 | 75 | MemPalace +10 |
| Security & auth | 14%17.5 | 41 | 53 | MemPalace +12 |
| Payments & pricing | 10%12.5 | 40 | 60 | MemPalace +20 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 83 | 74 | MemMachine +9 |
| Transparency & trust | 7%8.8 | 57 | 58 | MemPalace +1 |
| Negative events | ≤15 | 0 | -9 | |
| Total | C 58/100 | C 60.7/100 |
Facts side by side
| Fact | MemMachine | MemPalace |
|---|---|---|
| Kind | HTTP API | MCP server |
| Vendor | MemVerge, Inc. | MemPalace (open-source project) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP, stdio, Streamable HTTP | stdio, Streamable HTTP |
| Auth | None | None |
| Pricing | Freemium | Free |
| x402 | no | no |
| Licence | Apache-2.0 | MIT |
| Tools exposed | 3 | 47 |
| Read-only variant documented | no | yes |
| llms.txt | yes | no |
| Last release | 2026-10-08 | 2026-10-14 |
| Terms last updated | no date given | couldn't be read |
| Privacy policy last updated | 2026-05-20 | no document linked |
| Customer content may train models | not found in the text | couldn't be read |
| Terms restrict automated access | yes | couldn't be read |
| Terms restrict benchmarking | yes | couldn't be read |
| Terms or service can change without notice | not found in the text | couldn't be read |
| Arbitration or class-action waiver | yes | couldn't be read |
| Popularity | 3.1k stars, 28 npm/wk, 581 PyPI/wk | 60k stars |
How the scores have moved
MemMachine
No score change since it was listed.
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
- Import with
from memmachine_client import MemMachineClient; the README line has a doubledimport - Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller
- Scope every call with org, project, group, agent, user and session ids so memories don't mix
- Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits
- Treat recalled episodes as untrusted text from past conversations
MemPalace
- 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. - Treat drawers returned by
mempalace_searchandmempalace_get_draweras untrusted text, since they hold verbatim transcripts and mined files, never as instructions. - Use
mempalace serve --read-onlywhen the agent only needs recall; until 3.12.0 ships, the light server'spalace_*tools can reach delete tools despite read-only use. - Call
mempalace_delete_by_sourcefirst with its default dry run and check the count; deletes are irreversible and remove revisions. - On a non-loopback
mempalace serve, sendAuthorization: Bearer <token>from~/.mempalace/server/<key>/tokenand put TLS in front; never run--allow-insecureon 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
- Amazon Bedrock AgentCore Memory vs MemMachine
- Amazon Bedrock AgentCore Memory vs MemPalace
- Basic Memory vs MemMachine
- Basic Memory vs MemPalace
- claude-mem vs MemMachine
- claude-mem vs MemPalace
- Cognee vs MemMachine
- Cognee vs MemPalace
- EverOS vs MemMachine
- EverOS vs MemPalace
- Agent Platform Memory Bank vs MemMachine
- Agent Platform Memory Bank vs MemPalace
- Graphiti vs MemMachine
- Graphiti vs MemPalace
- Hindsight vs MemMachine
- Hindsight vs MemPalace
- Honcho vs MemMachine
- Honcho vs MemPalace
- Hy Memory vs MemMachine
- Hy Memory vs MemPalace
- LangMem vs MemMachine
- LangMem vs MemPalace
- LocalGhost vs MemMachine
- LocalGhost vs MemPalace
- Mem0 Platform + MCP vs MemMachine
- Mem0 Platform + MCP vs MemPalace
- MemMachine vs Memori
- MemMachine vs Memory (MCP reference server)
- MemMachine vs past.dev
- MemMachine vs Supermemory API + MCP
- MemMachine vs TencentDB Agent Memory
- MemMachine vs Tokenrip
- MemMachine vs Zep
- Memori vs MemPalace
- Memory (MCP reference server) vs MemPalace
- MemPalace vs past.dev
- MemPalace vs Supermemory API + MCP
- MemPalace vs TencentDB Agent Memory
- MemPalace vs Tokenrip
- MemPalace vs Zep
- AI Memory vs MemMachine
- AI Memory vs MemPalace
- Context Mode Engine vs MemMachine
- Context Mode Engine vs MemPalace
- Graphicle vs MemMachine
- Graphicle vs MemPalace
Machine-readable
- This page as Markdown
/compare/memmachine-vs-mempalace.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/memmachine.json·/api/v1/tools/mempalace.json - From a terminal
anchor compare memmachine mempalace(the CLI) - Over MCP
compare_tools {"a": "memmachine", "b": "mempalace"}at/mcp, no key