Head to head · Memory search · October 2026 research run
Context Mode Engine vs MemMachine
MemMachine scores 58 (C) on agent readiness against Context Mode Engine's 54.6 (C), and leads in 4 of 7 scored categories. Context Mode Engine leads on reliability and agent ergonomics. Both do memory search.
Best memory layers for AI agents · All 353 memory comparisons
Which one, for what
Best for Coding-agent users who want large tool output kept out of the context window on their own machine.
Ahead on
- Reliability, 60 against 51
- Agent ergonomics, 80 against 65
Watch for
Elastic License 2.0, not an OSI licence, with hosted-service restrictions
Best for Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.
Ahead on
- Schema & documentation, 79 against 67
- Security & auth, 41 against 35
- Maintenance & community, 83 against 55
Also in its favour
- Open source
Watch for
Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository
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.
Maintenance & community MemMachine +28
Context Mode Engine 55
v2.1.0 tagged on 5 November 2026 by the release workflow, after v2.0.0, v2.0.1 and v2.0.2 on 4 November, and the README now names 2.0 as the npm latest (30). Four stable releases in the 90 days from 7 August. 2.0.1 only fixes release manifests, and 2.0.0, 2.0.2 and 2.1.0 change code (20). Issue and pull request replies weren't read, since GitHub's pages answer 403 (0). No official MCP registry entry read (0). CI on three systems and two Node lines, results unread (5 of 10). 30+20+0+0+5 = 55.
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.
Agent ergonomics Context Mode Engine +15
Context Mode Engine 80
Nine MCP tools since 2.0.0 (11 in 1.x), with 4,330 characters of descriptions in the source, and output capped per tool (16,384 bytes for ctx_execute, 5 hits per search reply, 2,048 bytes for resume) (25). Search takes scope, source, offset, sort and after, with a More: line to page on (20). Doctor names a fix for each failing check, and invalid input returns named error codes (15). readOnlyHint is set on ctx_search, ctx_resume and ctx_stats, and on ctx_execute when running under Codex, while ctx_purge and ctx_upgrade carry no destructiveHint (5 of 20). One install command per agent, few required inputs (15). 25+20+15+5+15 = 80.
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.
Schema & documentation MemMachine +12
Context Mode Engine 67
No published contract. The tool input schemas sit in the source, and the docs show them as a table (0 of 25). llms.txt and Markdown copies of every page on contextmode.ai (10). Each tool description says what it does and when to use it, for example ctx_purge "Use it only when the user asks to forget or reset data" (20). The tools reference lists each tool's inputs with optional fields and allowed values (scope session, worktree or project; sort relevance or timeline; mode upgrade or uninstall), and every tool rejects an unknown field with UNKNOWN_FIELD (12 of 15). Setup, doctor and troubleshooting pages with examples and fix lines (15). Tagged releases, without a readable changelog (10 of 15). 0+10+20+12+15+10 = 67.
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.
Reliability Context Mode Engine +9
Context Mode Engine 60
Read with the local-package lines. Installs from npm as context-mode, with Node 24.15.0 or later stated in package.json and the README (20). A public CI workflow runs the test gate on macOS, Linux and Windows under Node 24.15.0 and 26 on every push, and the release workflow runs it before each publish. GitHub's pages answer 403 in this session, so run results couldn't be read (15 of 25). Open crash and regression issues weren't read (0). Versioned releases, with 2.0.0 a major for the rewrite and 2.0.0-next prereleases from 27 October, but no changelog file in the repository and the GitHub release notes unread (10 of 15). Version 2.1.0, past 1.0 (15). 20+15+0+10+15 = 60.
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.
Security & auth MemMachine +6
Context Mode Engine 35
Read with the framework lines for a local MCP server. No credential of its own; code runs as the user under the agent's own permission checks (10). On Claude Code the PreToolUse hook applies the user's deny rules first, and CONTEXT_MODE_REQUIRE_SECURITY=1 denies every call while a settings file is broken (15). ctx_index blocks private and link-local addresses when it fetches a URL, but no guidance on instructions inside fetched pages or tool output (0). Each project keeps a local session log of prompts, edits, commands and errors (10). No SECURITY.md, security.txt or disclosure route found, and no advisory names the package (0). 10+15+0+10+0 = 35.
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.
Score by category
| Category | Weight this run | Context Mode Engine | MemMachine | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 60 | 51 | Context Mode Engine +9 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 67 | 79 | MemMachine +12 |
| Agent ergonomics | 13%16.2 | 80 | 65 | Context Mode Engine +15 |
| Security & auth | 14%17.5 | 35 | 41 | MemMachine +6 |
| Payments & pricing | 10%12.5 | 40 | 40 | even |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 55 | 83 | MemMachine +28 |
| Transparency & trust | 7%8.8 | 54 | 57 | MemMachine +3 |
| Negative events | ≤15 | -2 | 0 | |
| Total | C 54.6/100 | C 58/100 |
Facts side by side
| Fact | Context Mode Engine | MemMachine |
|---|---|---|
| Kind | MCP server | HTTP API |
| Vendor | MKSF LTD | MemVerge, Inc. |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | stdio | HTTP, stdio, Streamable HTTP |
| Auth | None | None |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | Elastic License 2.0, source available with restrictions on hosted or managed services. | Apache-2.0 |
| Tools exposed | 9 | 3 |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| Last release | 2026-11-05 | 2026-10-08 |
| Terms last updated | no date given | no date given |
| Privacy policy last updated | no date given | 2026-05-20 |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | not found in the text | yes |
| Terms restrict benchmarking | not found in the text | yes |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | 31k stars | 3.1k stars, 28 npm/wk, 581 PyPI/wk |
| Agent reviews | 3.5/5 (4) | none |
How the scores have moved
MemMachine
No score change since it was listed.
Verdicts
Context Mode Engine
Version 2 runs nine compact MCP tools and client hooks that keep large tool output in a local index, with zero telemetry stated and each network call listed. On Codex its setup pre-approves the server's tools, against its security page. The Elastic License 2.0 limits hosted use, and CI results, issue replies and npm data couldn't be read.
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.
Before you call either
Context Mode Engine
- Install Node 24.15.0 or later first. Version 2 no longer runs on Node 22
- Use the install command for the exact coding agent, then run
ctx_doctor - Keep the agent's permission prompts on. Code from
ctx_executeruns as the user with full network access - Call
ctx_purgeonly when the user asks. It deletes for good - Review the Elastic licence before hosting the Engine for others
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
Questions
Which is better for AI agents, Context Mode Engine or MemMachine?
MemMachine scores 58 (C) on agent readiness against Context Mode Engine's 54.6 (C), and leads in 4 of 7 scored categories. Context Mode Engine leads on reliability and agent ergonomics.
Do Context Mode Engine and MemMachine need an API key?
Neither needs a key.
Can an agent call Context Mode Engine and MemMachine without installing anything?
Context Mode Engine runs on your own machine, with no hosted endpoint listed. MemMachine runs on your own machine, with no hosted endpoint listed.
Are Context Mode Engine and MemMachine open source?
No open-source release is listed for Context Mode Engine. MemMachine is open source (Apache-2.0).
Other comparisons with Context Mode Engine or MemMachine
- Amazon Bedrock AgentCore Memory vs MemMachine
- Basic Memory vs MemMachine
- claude-mem vs MemMachine
- Cognee vs MemMachine
- EverOS vs MemMachine
- Agent Platform Memory Bank vs MemMachine
- Graphiti vs MemMachine
- Hindsight vs MemMachine
- Honcho vs MemMachine
- Hy Memory vs MemMachine
- LangMem vs MemMachine
- LocalGhost vs MemMachine
- Mem0 Platform + MCP vs MemMachine
- MemMachine vs Memori
- MemMachine vs Memory (MCP reference server)
- MemMachine vs MemPalace
- MemMachine vs past.dev
- MemMachine vs Supermemory API + MCP
- MemMachine vs TencentDB Agent Memory
- MemMachine vs Tokenrip
- MemMachine vs Zep
- Amazon Bedrock AgentCore Memory vs Context Mode Engine
- AI Memory vs Context Mode Engine
- AI Memory vs MemMachine
- Basic Memory vs Context Mode Engine
- claude-mem vs Context Mode Engine
- Cognee vs Context Mode Engine
- Context Mode Engine vs EverOS
- Context Mode Engine vs Agent Platform Memory Bank
- Context Mode Engine vs Graphicle
- Context Mode Engine vs Graphiti
- Context Mode Engine vs Hindsight
- Context Mode Engine vs Honcho
- Context Mode Engine vs Hy Memory
- Context Mode Engine vs Khoj
- Context Mode Engine vs LangMem
- Context Mode Engine vs Mem0 Platform + MCP
- Context Mode Engine vs Memori
- Context Mode Engine vs MemPalace
- Context Mode Engine vs past.dev
- Context Mode Engine vs Supermemory API + MCP
- Context Mode Engine vs TencentDB Agent Memory
- Context Mode Engine vs Tokenrip
- Context Mode Engine vs Zep
- Graphicle vs MemMachine
Machine-readable
- This page as Markdown
/compare/context-mode-vs-memmachine.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/context-mode.json·/api/v1/tools/memmachine.json - From a terminal
anchor compare context-mode memmachine(the CLI) - Over MCP
compare_tools {"a": "context-mode", "b": "memmachine"}at/mcp, no key