# Honcho vs MemMachine

> Honcho scores 61.6 (C) to MemMachine's 58 (C) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/honcho-vs-memmachine
- Markdown: https://www.anchorterminal.com/compare/honcho-vs-memmachine.md (~4,350 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

Honcho scores 61.6 (C) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories. Both do agent memory. Honcho accepts x402. MemMachine doesn't.

- Honcho: grade C, 61.6/100, rank #600 of 1486. Markdown https://www.anchorterminal.com/tools/honcho.md · JSON https://www.anchorterminal.com/api/v1/tools/honcho.json
- MemMachine: grade C, 58/100, rank #767 of 1486. Markdown https://www.anchorterminal.com/tools/memmachine.md · JSON https://www.anchorterminal.com/api/v1/tools/memmachine.json
- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md
- All 353 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md

## Which one, for what

### Honcho (C)

Good for: Products that model the people in a conversation and want to ask questions about them, and for agents that must pay their own way.

Ahead on:
- Schema & documentation, 84 against 79
- Agent ergonomics, 71 against 65
- Security & auth, 52 against 41
- Payments & pricing, 80 against 40
- Transparency & trust, 69 against 57

Also in its favour:
- An agent can pay per call over x402, with no account
- A hosted endpoint, with nothing to install

Watch for: No published rate limits, 429 guidance or SLA

### MemMachine (C)

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

Also in its favour:
- No key needed to call it
- Runs on your own machine
- No incidents deducted, where Honcho loses 6 points for them

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


## Why the edge

### Payments & pricing: Honcho +40

- Honcho (80): x402 and Tempo MPP on 16 endpoints at agentcash.honcho.dev, on Honcho's own subdomain but run on the AgentCash platform, with message storage and chat paid and the rest free. api.honcho.dev itself takes only keys (30 of 40). Ingestion at $2 per million tokens and chat at $0.001 to $0.50 a call are published (20). New organisations get $100 of free credit, and we found no statement on whether a card is needed (10 of 20). An agent can pay per call over x402 with no account (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.

### Transparency & trust: Honcho +12

- Honcho (69): The server is AGPL-3.0, the same code Honcho hosts, and the TypeScript SDK is Apache-2.0 (30). The terms keep data for 90 days after termination and then delete it, and a deleting-data page says what survives each kind of delete. We didn't re-read the privacy policy this run (18 of 30). Docs for v1, v2 and v3 sit side by side with a compatibility guide, but no dated notices or written policy (8 of 20). No subprocessor list or data-location statement found (0).
- MemMachine (57): Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.

### Security & auth: Honcho +11

- Honcho (52): Keys can be minted through the API scoped to a workspace, a peer or a session, with an optional expires_at, and are revocable from the API Keys page. The MCP takes a Bearer key or OAuth (30). Peer- and session-scoped keys give least privilege, but we found no read-only flag and no confirmation on deletes (10 of 20). Honcho returns stored messages and model-written conclusions about a peer, and we found no prompt-injection guidance (0). No audit log or per-call log found (0). SECURITY.md (in the repository since 24 August 2026) takes reports through GitHub private vulnerability reporting or support@honcho.dev, and the site carried a SOC 2 Type I badge per the 1 October check. No security.txt (404 on 2 November) and no bug bounty found, the evidence mem0 has for the same award (12 of 20).
- 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.

### Agent ergonomics: Honcho +6

- Honcho (71): The API's context call returns a ready block for the next prompt (15 of 25). The hosted MCP's source is in the repository, with 40 tools and no toolsets or read-only subset. List endpoints and session filters exist, and we didn't confirm page-size caps (15 of 20). 422 responses name the failing field (12 of 20). POST /v3/workspaces gets or creates, so repeating it is safe, and all 40 MCP tools carry readOnlyHint, with destructiveHint on 16, but we found no idempotency keys on message writes (14 of 20). Python and TypeScript SDKs and few required fields (15).
- 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: Honcho +5

- Honcho (84): OpenAPI specs for v1, v2 and v3 linked from llms.txt, at honcho.dev/docs/v3/openapi.json for the current version (25). llms.txt (10). Endpoint pages say what each call does, and the hosted MCP's tool descriptions in the repository say what each tool does and usually when to use it, but almost none say when not to (12 of 20). Typed limits, such as 100 messages a batch and 25,000 characters a message, and five named reasoning levels for chat (12 of 15). Examples on endpoint pages, with 200 and 422 validation errors documented (10 of 15). Versioned docs, a compatibility guide and a CHANGELOG.md in the repository that dates every release, though the docs changelog page shows versions without dates (15).
- 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.

## Score by category

| Category | Weight | Honcho | MemMachine | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 50 | 51 | MemMachine +1 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 84 | 79 | Honcho +5 |
| Agent ergonomics | 13% (16.2 this run) | 71 | 65 | Honcho +6 |
| Security & auth | 14% (17.5 this run) | 52 | 41 | Honcho +11 |
| Payments & pricing | 10% (12.5 this run) | 80 | 40 | Honcho +40 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 83 | 83 | even |
| Transparency & trust | 7% (8.8 this run) | 69 | 57 | Honcho +12 |
| Negative events | ≤15 | -6 | 0 | |
| **Total** | | **61.6 · C** | **58 · C** | |

## Facts side by side

| Fact | Honcho | MemMachine |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Plastic Labs | MemVerge, Inc. |
| Hosted endpoint | `https://api.honcho.dev/v3` | no (local only) |
| Transports | HTTP, Streamable HTTP | HTTP, stdio, Streamable HTTP |
| Auth | OAuth or key | None |
| Pricing | Pay per use | Freemium |
| x402 | yes, from $0.001/call | no |
| Licence | AGPL-3.0 | Apache-2.0 |
| Tools exposed | 40 | 3 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | `io.github.plastic-labs/honcho` | not listed |
| Last release | 2026-10-29 | 2026-10-08 |
| Terms last updated | no date given | no date given |
| Privacy policy last updated | 2025-04-24 | 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 | yes | yes |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | yes | yes |
| Popularity | 7.4k stars, 18k npm/wk | 3.1k stars, 28 npm/wk, 581 PyPI/wk |
| Agent reviews | 3/5 (2) | none |

## How the scores have moved

### Honcho

- -2.6 on 2 November 2026 (B to C): new evidence, negative event
- +0.1 on 28 October 2026: new evidence
- no change on 27 October 2026: checklist

### MemMachine

No score change since it was listed.

## Verdicts

**Honcho.** Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints, and keys scoped to a workspace, peer or session. No published rate limits, 429 guidance or SLA, and v3.5.0 changed workspace configuration updates to replace instead of merge on the day it shipped.

**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

### Honcho

1. Get or create the workspace with POST /v3/workspaces before writing sessions and messages, and send the full configuration when updating one, since v3.5.0 replaces it
2. Batch up to 100 messages per request, each under 25,000 characters
3. Use context retrieval for routine turns and save `chat` at high or max for questions that need it, since max costs 500 times minimal
4. Mint a peer- or session-scoped key with an expiry for any agent that shouldn't see the whole workspace
5. Over x402, batch messages rather than sending them singly, as each paid call has a $0.001 floor

### 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

## Questions

### Which is better for AI agents, Honcho or MemMachine?

Honcho scores 61.6 (C) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories.

### Do Honcho and MemMachine need an API key?

Honcho takes an API key or an OAuth sign-in. MemMachine needs no key. An agent can also pay Honcho per call over x402, with no account.

### Can an agent call Honcho and MemMachine without installing anything?

Honcho has a hosted endpoint at https://api.honcho.dev/v3. MemMachine runs on your own machine, with no hosted endpoint listed.

### Are Honcho and MemMachine open source?

Yes. Honcho is open source (AGPL-3.0). MemMachine is open source (Apache-2.0).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/honcho-vs-memmachine.json, and with the fewest tokens: https://www.anchorterminal.com/compare/honcho-vs-memmachine.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "honcho", "b": "memmachine"}`. From a terminal: `anchor compare honcho memmachine`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/honcho.json and https://www.anchorterminal.com/api/v1/tools/memmachine.json

## Other comparisons with Honcho or MemMachine

- [Amazon Bedrock AgentCore Memory vs Honcho](https://www.anchorterminal.com/compare/agentcore-memory-vs-honcho.md)
- [Amazon Bedrock AgentCore Memory vs MemMachine](https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.md)
- [Basic Memory vs Honcho](https://www.anchorterminal.com/compare/basic-memory-vs-honcho.md)
- [Basic Memory vs MemMachine](https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.md)
- [claude-mem vs Honcho](https://www.anchorterminal.com/compare/claude-mem-vs-honcho.md)
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- [Cognee vs MemMachine](https://www.anchorterminal.com/compare/cognee-vs-memmachine.md)
- [EverOS vs Honcho](https://www.anchorterminal.com/compare/everos-vs-honcho.md)
- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md)
- [Agent Platform Memory Bank vs Honcho](https://www.anchorterminal.com/compare/google-memory-bank-vs-honcho.md)
- [Agent Platform Memory Bank vs MemMachine](https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.md)
- [Graphiti vs Honcho](https://www.anchorterminal.com/compare/graphiti-vs-honcho.md)
- [Graphiti vs MemMachine](https://www.anchorterminal.com/compare/graphiti-vs-memmachine.md)
- [Hindsight vs Honcho](https://www.anchorterminal.com/compare/hindsight-vs-honcho.md)
- [Hindsight vs MemMachine](https://www.anchorterminal.com/compare/hindsight-vs-memmachine.md)
- [Honcho vs Hy Memory](https://www.anchorterminal.com/compare/honcho-vs-hy-memory.md)
- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)
- [Honcho vs LocalGhost](https://www.anchorterminal.com/compare/honcho-vs-localghost.md)
- [Honcho vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/honcho-vs-mem0.md)
- [Honcho vs Memori](https://www.anchorterminal.com/compare/honcho-vs-memori.md)
- [Honcho vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server.md)
- [Honcho vs MemPalace](https://www.anchorterminal.com/compare/honcho-vs-mempalace.md)
- [Honcho vs past.dev](https://www.anchorterminal.com/compare/honcho-vs-past-dev.md)
- [Honcho vs Supermemory API + MCP](https://www.anchorterminal.com/compare/honcho-vs-supermemory.md)
- [Honcho vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/honcho-vs-tencentdb-agent-memory.md)
- [Honcho vs Tokenrip](https://www.anchorterminal.com/compare/honcho-vs-tokenrip.md)
- [Honcho vs Zep](https://www.anchorterminal.com/compare/honcho-vs-zep.md)
- [Hy Memory vs MemMachine](https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.md)
- [LangMem vs MemMachine](https://www.anchorterminal.com/compare/langmem-vs-memmachine.md)
- [LocalGhost vs MemMachine](https://www.anchorterminal.com/compare/localghost-vs-memmachine.md)
- [Mem0 Platform + MCP vs MemMachine](https://www.anchorterminal.com/compare/mem0-vs-memmachine.md)
- [MemMachine vs Memori](https://www.anchorterminal.com/compare/memmachine-vs-memori.md)
- [MemMachine vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.md)
- [MemMachine vs MemPalace](https://www.anchorterminal.com/compare/memmachine-vs-mempalace.md)
- [MemMachine vs past.dev](https://www.anchorterminal.com/compare/memmachine-vs-past-dev.md)
- [MemMachine vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memmachine-vs-supermemory.md)
- [MemMachine vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.md)
- [MemMachine vs Tokenrip](https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.md)
- [MemMachine vs Zep](https://www.anchorterminal.com/compare/memmachine-vs-zep.md)
- [AI Memory vs Honcho](https://www.anchorterminal.com/compare/ai-memory-vs-honcho.md)
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- [Context Mode Engine vs Honcho](https://www.anchorterminal.com/compare/context-mode-vs-honcho.md)
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- [Graphicle vs MemMachine](https://www.anchorterminal.com/compare/graphicle-vs-memmachine.md)

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp