Looking for a mem0 alternative?
mem0 gives your agent memory. FoxNose gives it a knowledge base — structured storage, hybrid search, and an embedded MCP server behind one endpoint. Not just what a user said last week, but the catalogs, docs, tickets, and policies your agent answers from.
FoxNose and mem0, line by line
Same category — a knowledge and memory backend for agents. Here is how the two compare on the numbers and the architecture.
| FoxNose | mem0 | |
|---|---|---|
| Entry price | Free — $0: 10K retrievals + 5K writes + 0.5 GB data + 0.1 GB vector (~26K records) | Hobby — $0: 1K retrieval requests/mo, 10K add requests/mo |
| Retrievals at $19/mo | 75,000 (Starter) | 5,000 (Starter) |
| Retrievals at top self-serve tier | 400,000 — Pro, $99/mo | 50,000 — Pro, $249/mo |
| What's metered | Four axes: retrievals, writes, data storage, vector storage | Retrieval requests and add requests; end users are unmetered on every tier |
| Capability gating | None — every feature is on every tier; plans differ by scale | Hobby & Starter are capped at 1 project with no advanced analytics; unlimited projects and advanced analytics arrive on Pro ($249) |
| MCP architecture | Embedded MCP server per API — read and write tools (agents save memories through the same connector), same host, same auth as REST | Hosted MCP server at a separate endpoint (mcp.mem0.ai) |
| Data residency | EU-hosted; embeddings never leave the EU (Cohere multilingual via AWS Bedrock EU) | US-based pipeline |
| Search types | Structured + keyword + semantic fused in one call | Memory retrieval, plus built-in graph memory (entity linking) |
| Per-user scoping (multi-tenancy) | Enforced by the data layer: strict-reference collections put the tenant in the URL, ownership is verified per request, and deleting a user cascades to all their memories, embeddings included | Scoped by user_id / agent_id passed on each write and query — correct isolation depends on your app passing the right IDs on every call |
| Surprise-bill protection | 4xx and error responses are never billed; spend cap defaults to 2× the plan; Free stops per axis with a 402 | Overage and spend-cap behaviour not stated on their pricing page |
What a dollar buys in retrievals
Retrievals are the line that scales with agent traffic. Here is the arithmetic on the two tiers most teams compare, so you can reproduce it.
75,000 ÷ 5,000 = 15× the retrievals at the same $19, before counting FoxNose's 20,000 writes and 5 GB of storage on the same plan.
400,000 ÷ 50,000 = 8× the retrievals, and $99 ÷ $249 ≈ 40% of the price.
Cases where mem0 is the better pick
Graph memory out of the box
mem0 ships built-in graph memory (entity linking). FoxNose fuses structured, keyword, and semantic search in one call, but it is not a graph store — if your model needs a memory graph, mem0 has it built in.
Automatic memory extraction
mem0 runs an LLM over your conversations to extract and deduplicate memories automatically. FoxNose stores what your agent explicitly writes — predictable and schema-validated, but the "what is worth remembering" logic is yours (or your agent's) to own.
Per-end-user memory with unmetered end users
mem0 does not meter end users on any tier. If your product is a per-user personal-memory assistant with high end-user fan-out, that billing shape can work out cheaper than metering retrievals.
A US processing preference
mem0 runs a US-based pipeline. FoxNose is EU-hosted today, with embeddings kept in the EU. If you specifically want data processed in the US, mem0 matches that.
Try the knowledge backend
Start on the Free tier — 10,000 retrievals and 5,000 writes, no credit card. Point your agent at REST or the embedded MCP server and see how it fits.
Frequently asked questions
- Is FoxNose a drop-in replacement for mem0?
- It depends on what you use mem0 for. FoxNose is a knowledge base with hybrid search and an embedded MCP server — structured knowledge your agent queries to answer end-users. If you use mem0 to store business knowledge (catalogs, docs, tickets, policies) that an agent retrieves, FoxNose covers that directly. Per-end-user memory works too: strict-reference collections scope each user's memories at the data layer, and agents write them through the same MCP connector. The remaining difference is memory extraction — mem0 runs an LLM over conversations to decide what to remember; with FoxNose, your agent decides what to write. See "Where mem0 fits better" above.
- How do the free tiers compare?
- FoxNose Free is $0 and includes 10,000 retrievals, 5,000 writes, 0.5 GB of data storage, and 0.1 GB of vector storage — roughly 26,000 records. mem0 Hobby is $0 with 1,000 retrieval requests per month and 10,000 add requests per month. Both are usable without a credit card.
- What do I get for $19 a month?
- FoxNose Starter is $19/mo and includes 75,000 retrievals, 20,000 writes, 5 GB of data, and 1 GB of vector storage (~260K records). mem0 Starter is $19/mo with 5,000 retrieval requests and 50,000 add requests. On the retrievals line that is 75,000 ÷ 5,000 = 15× the retrievals for the same price. No FoxNose feature is gated behind a higher tier.
- Where is my data processed?
- FoxNose is EU-hosted, and embeddings never leave the EU — they run on Cohere multilingual through AWS Bedrock in-region, with no US round-trip. mem0 runs a US-based pipeline. If you have EU data-residency requirements, FoxNose keeps the whole path in the EU; if you specifically prefer US processing, mem0 fits that.
- Will I get a surprise bill?
- On FoxNose, requests that return 4xx or error responses are never billed, and the spend cap defaults to twice the plan price ($38 on Starter, $198 on Pro) — you can set it anywhere from $0 to $500. On the Free plan each axis stops independently with an HTTP 402 rather than silently charging you. This keeps overage bounded to a number you set.
Competitor pricing checked July 23, 2026; see their pricing pages for current numbers.