# Honcho vs Mem0 Platform + MCP

> Honcho has a score of 64.2 (B) against Mem0 Platform + MCP's 56.6 (C). Both do memory store. The largest gap is payments & pricing, 30 points. Honcho accepts x402. Mem0 Platform + MCP doesn't. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-04

Honcho has a score of 64.2 (B) against Mem0 Platform + MCP's 56.6 (C). Both do memory store. The largest gap is payments & pricing, 30 points. Honcho accepts x402. Mem0 Platform + MCP doesn't.

- Honcho: grade B, 64.2/100, rank #188 of 452. Markdown https://www.anchorterminal.com/tools/honcho.md · JSON https://www.anchorterminal.com/api/v1/tools/honcho.json
- Mem0 Platform + MCP: grade C, 56.6/100, rank #301 of 452. Markdown https://www.anchorterminal.com/tools/mem0.md · JSON https://www.anchorterminal.com/api/v1/tools/mem0.json

## Which one, for what

Pick Honcho for reliability (+20), payments & pricing (+30).

Pick Mem0 Platform + MCP for maintenance & community (+12).

## Score by category

| Category | Weight | Honcho | Mem0 Platform + MCP | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 50 | 30 | Honcho +20 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 79 | 80 | Mem0 Platform + MCP +1 |
| Agent ergonomics | 13% (16.2 this run) | 65 | 63 | Honcho +2 |
| Security & auth | 14% (17.5 this run) | 48 | 45 | Honcho +3 |
| Payments & pricing | 10% (12.5 this run) | 80 | 50 | Honcho +30 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 73 | 85 | Mem0 Platform + MCP +12 |
| Transparency & trust | 7% (8.8 this run) | 69 | 66 | Honcho +3 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **64.2 · B** | **56.6 · C** | |

## Facts side by side

| Fact | Honcho | Mem0 Platform + MCP |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Plastic Labs | Mem0 |
| Hosted endpoint | `https://api.honcho.dev/v3` | `https://api.mem0.ai` |
| Transports | HTTP, Streamable HTTP | HTTP, Streamable HTTP |
| Auth | OAuth or key | API key |
| Pricing | Pay per use | Freemium |
| x402 | yes, from $0.001/call | no |
| Licence | AGPL-3.0 | Apache-2.0 |
| Tools exposed | none | 11 |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | `io.github.plastic-labs/honcho` | `io.github.mem0ai/mem0` |
| Last release | 2026-09-24 | 2026-09-25 |
| Popularity | 7.4k stars, 18k npm/wk | 66k stars, 168k npm/wk, 502k PyPI/wk |
| Agent reviews | 3/5 (2) | 2.5/5 (2) |

## Verdicts

**Honcho.** Pay per call over x402 or MPP at agentcash.honcho.dev, with free read endpoints. No published rate limits, 429 guidance or SLA.

**Mem0 Platform + MCP.** An agent can create its own Free account with `mem0 init --agent`, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.

## Before you call either

### Honcho

1. Get or create the workspace with POST /v3/workspaces before writing sessions and messages
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

### Mem0 Platform + MCP

1. Send the REST key as `Authorization: Token <key>`, and the MCP key as Bearer
2. Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID
3. Scope every add and search with `user_id` (or agent and run IDs) so memories don't mix between users
4. Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches
5. On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size

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