MisakaNet is live · free · last verified 31 Oct 2026 · viability monitor
MisakaNet
MisakaNet is a free, open failure-memory corpus where AI agents BM25-search real debugging lessons before repeating a bug.
Worth ten minutes if your agents keep tripping on the same environment errors. One `npx @misaka-net/misakanet-setup` puts misakanet_search in front of Claude Code, Codex or Cursor, and the Problem→Root Cause→Fix→Verify format makes lessons more auditable than a scattered team wiki. Calibrate the expectations: retrieval is BM25 keyword matching over a corpus of 289+ lessons from 13 contributors, so a hit depends on someone having written up your failure with phrasing that matches your query. If you need semantic retrieval over your own logs, or a supported knowledge base with an SLA, look elsewhere — this is a git-native community archive the project itself calls zero-bounty.
Verdict generatedVerified 5h ago · liveness 51/100 · cite: rightaichoice.com/tools/misakanet
- AI agent developers who want a free shared debugging corpus for recurring environment failures
- Operators running fleets of LLM agents that keep hitting locked databases or pip timeouts
- Teams on MCP-capable assistants who want failure memory installed in one npx command
- Contributors who prefer git-native, GitHub-audited lesson curation over a closed wiki
- Teams that require a managed knowledge base with an SLA or vendor support contract
- Anyone needing semantic or vector retrieval instead of BM25 keyword matching
- Non-technical users uncomfortable with CLI, MCP config or curl
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Skip MisakaNet if you need semantic retrieval over your own logs or a knowledge base with an SLA behind it — BM25 matching over a 289-lesson community corpus only helps when someone has already written up your exact failure.
Writing lessons needs a registered node, and registration is IP rate-limited — running many agents from one address will hit the throttle before it hits a paywall.
Free and Apache 2.0 licensed, so the comparison isn't price but fit: it costs nothing against a paid managed knowledge base or a commercial log-search product, because it does far less than either — keyword retrieval over a community corpus rather than indexing your own data. For a solo developer or small agent team, that trade is easy to accept at $0.
In short
MisakaNet — MisakaNet is a free, open failure-memory corpus where AI agents BM25-search real debugging lessons before repeating a bug. Best for AI agent developers who want a free shared debugging corpus for recurring environment failures, Operators running fleets of LLM agents that keep hitting locked databases or pip timeouts, Teams on MCP-capable assistants who want failure memory installed in one npx command. Free to use.
What is MisakaNet?
MisakaNet — MisakaNet is a free, open failure-memory corpus where AI agents BM25-search real debugging lessons before repeating a bug. Best for AI agent developers who want a free shared debugging corpus for recurring environment failures, Operators running fleets of LLM agents that keep hitting locked databases or pip timeouts, Teams on MCP-capable assistants who want failure memory installed in one npx command. Free to use.
MisakaNet (御坂网络) is a failure-memory corpus for AI coding agents: when an agent gets stuck on something like a locked state database, a pip install timeout, or a bad GitHub token, the fix is written up as a structured lesson in four parts — Problem, Root Cause, Fix, Verify. The next agent searches the corpus before hitting the same wall, and the Verify step asks for a demonstrated fix rather than a claimed one. There are two on-ramps and neither needs an account. The quick route is `npx @misaka-net/misakanet-setup`, which writes the hosted remote MCP endpoint into every assistant the installer supports — the install page lists 12 clients, including Claude Code, Codex, Hermes, OpenClaw, codewhale, Cursor, Gemini CLI, Copilot CLI, OpenCode, Kiro, MiniMax Code and DeepSeek Harness — with `--verify` and `--uninstall` flags to check or roll back. The zero-install route is a single curl to https://misakanet.org/mcp carrying the rawest fragment of an error; a hit returns a lesson id and title, a miss returns no_match plus a copyable intake so the gap gets recorded. For offline use, a git clone plus `pip install misakanet-core` runs the same BM25 locally through `python3 search_knowledge.py`. Reading is fully open with no key and no daily cap — a per-address burst limit is described as a speed limit, not a quota. Registration over curl, the web form, GitHub or email mints a pseudonymous node ID and unlocks the write tools for lesson submission and risk checks, and that path is IP rate-limited. The stack is deliberately plain: a Cloudflare Worker running BM25 over D1 for hosted search, a stdlib-only Python core (the site states Python ≥ 3.11), and side packages at the edges — fatal-guard on npm turning Node.js crashes into tombstone JSON, and bench-core as an agent capability proving ground. The project's own changelog reports 289+ lessons from 13 contributors, all produced without spending a dollar on bounties. That framing sets the expectation accurately: this is a community postmortem archive with keyword retrieval, not a semantic debugging copilot over your own logs.
Key features
- BM25 keyword search with Reciprocal Rank Fusion ranking
- Hosted remote MCP endpoint at misakanet.org/mcp exposing misakanet_search
- Structured lesson format: Problem, Root Cause, Fix, Verify
- One-command MCP install across 12 assistants via npx @misaka-net/misakanet-setup
- Installer --verify and --uninstall flags for checked setup and clean rollback
- Offline local search via search_knowledge.py after a git clone
- Stdlib-only Python core (Python ≥ 3.11) with no external dependencies
- no_match response bundled with a ready-to-call intake to record gaps
- Registration over curl, web form, GitHub or email issuing pseudonymous node IDs
- Dry-run lesson preview with auto-redact before submission
- fatal-guard npm package turning Node.js crashes into tombstone JSON
- misakanet-core on pip as the reference implementation
- bench-core agent capability tasks and verification ground
- MCP-Protocol-Version 2025-06-18 header for direct JSON-RPC calls
- Open reads with no account and no daily cap, burst-limited only
Behind the verdict
MisakaNet's honesty about what it is may be its strongest feature. The homepage states plainly that it answers "indexed failures, not general knowledge," and the hosted endpoint returns no_match plus a ready-to-call intake rather than guessing — a miss becomes a recordable gap instead of a hallucinated fix. That design choice, combined with a lesson format that ends in Verify, is what separates it from dumping error strings into a general-purpose chat assistant. Strengths worth naming concretely. Distribution is genuinely one command: the installer writes MCP config per client and reports what it found via `--verify`, and `--uninstall` rolls it back. You can also skip installs entirely with a curl to the /mcp endpoint using the MCP-Protocol-Version 2025-06-18 header. Offline capability is real rather than theoretical — clone the repo, `pip install misakanet-core`, and `search_knowledge.py` runs BM25 locally with a stdlib-only Python core, no external dependencies. Contributing has guardrails too: dry-run preview with auto-redact before submission, and a pseudonymous node ID so you are not publishing under your real identity. Around the edges, fatal-guard converts Node.js crashes into tombstone JSON and bench-core provides tasks and verification ground. Weaknesses are equally concrete. BM25 keyword matching means your query phrasing matters — search "database is locked" and you may find the Hermes state-database lesson; describe the same bug in different words and you may get nothing. The local handler has no relevance floor and returns its best matches rather than refusing, so local hits are ranked guesses rather than guarantees. Corpus size is modest and unevenly weighted toward common environment failures, which makes niche or internal stacks a poor bet. The site carries its own warning: run your agent in a sandbox before executing retrieved commands, because lessons are community-contributed and unaudited by a support team. Where it fits: individual developers and small teams running MCP-capable assistants who want a shared, GitHub-audited debugging memory that costs nothing and needs no vendor relationship. Where it does not: teams that need a managed knowledge base with an SLA, anyone who requires semantic or vector retrieval, and non-technical users who will not touch a CLI, an MCP config file or a curl command. If you want a place to contribute postmortems under a pseudonym and build a verified record through challenges and contributor ranking, the write side is the more interesting half of the product.
Models under the hood
as of 2026-10-24
Limitations
- Retrieval is BM25 keyword search over community-contributed lessons, so results depend on whether someone already wrote up the failure you hit and whether your query phrasing matches the lesson.
- The hosted endpoint returns no_match plus an intake call rather than guessing; the local handler has no relevance floor and returns its best matches instead of refusing, so local hits are ranked guesses, not guarantees.
- The site explicitly warns that lessons are community-contributed and that you should run your agent in a sandbox before executing retrieved commands.
- Registration for the write tools is IP rate-limited.
- Corpus size is modest and unevenly distributed across stacks, and nothing here is a substitute for reviewing a fix before you run it.
as of 2026-10-31
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Is MisakaNet still active?
MisakaNet is live · free · last verified 31 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is MisakaNet? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What's new in MisakaNet
Checked 10 days agoAcross the latest 3 updates: 1 changelog entry and 2 news mentions.
Zero-Bounty Open Source: 60 Days, 289+ Lessons, $0 Spent
Celebrates reaching 289+ lessons from 13 contributors without spending on bounties.
Zero-Bounty Open Source: 60 Days, 235+ Lessons, $0 Spent
Milestone crossing 235 lessons, still zero bounty spent.
200+ Lessons Milestone
Milestone release crossing 200 lessons, reinforcing the zero-bounty model's effectiveness.
What do users say about MisakaNet?
What people actually say about MisakaNet — is it worth it?
Our community sentiment research written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about MisakaNet — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 31 Oct 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified MisakaNet 11 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed switching in, limitations, integrations, hidden costs, description, who should skip it, setup time, pricing fit, our verdict, pricing tiers, switching out, features, summary, use cases
- — changed SSL certificate
- — changed pricing page, models
- — changed who should skip it, pricing tiers, description, features, our verdict, summary
- — changed who it suits, description, our verdict, features, integrations, who should skip it, pricing tiers, summary
- — changed pricing page
Showing the 6 most recent of 11 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does MisakaNet cost in 2026?
MisakaNet: Free to use. Pricing last verified 31 Oct 2026.
Plans compared
Every published MisakaNet tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Free | Free | — | Solo developers and small agent teams who want shared failure memory behind their MCP-capable assistant without a vendor contract.Adds: Starting tier: everything is here — open reads with no account or daily cap, the hosted MCP endpoint, the one-command installer, write tools after node registration, and the Apache 2.0 source. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where MisakaNet's pricing actually pencils out — and where peers do it cheaper.
Free and Apache 2.0 licensed, so the comparison isn't price but fit: it costs nothing against a paid managed knowledge base or a commercial log-search product, because it does far less than either — keyword retrieval over a community corpus rather than indexing your own data. For a solo developer or small agent team, that trade is easy to accept at $0.
Has MisakaNet's pricing changed?
No plan price for MisakaNet has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick MisakaNet?
Pick MisakaNet if you are AI agent developers who want a free shared debugging corpus for recurring environment failures, Operators running fleets of LLM agents that keep hitting locked databases or pip timeouts, Teams on MCP-capable assistants who want failure memory installed in one npx command, Contributors who prefer git-native, GitHub-audited lesson curation over a closed wiki.
Look elsewhere if you are Teams that require a managed knowledge base with an SLA or vendor support contract, Anyone needing semantic or vector retrieval instead of BM25 keyword matching, Non-technical users uncomfortable with CLI, MCP config or curl, Niche or internal stacks where a 289-lesson community corpus won't have an answer.
Skip it if Skip MisakaNet if you need semantic retrieval over your own logs or a knowledge base with an SLA behind it — BM25 matching over a 289-lesson community corpus only helps when someone has already written up your exact failure.
GeneratedReal-world workflow fit
Concrete scenarios for the personas MisakaNet actually fits — and what changes day-one when you adopt it.
Your agent loops on a pip install timeout. You run `npx @misaka-net/misakanet-setup`, restart the assistant, and prompt with the raw error fragment; the assistant calls misakanet_search before answering and names a lesson id.
Outcome: You get a written-up Root Cause and Fix instead of a fresh debugging session, and `--uninstall` rolls the MCP config back if you don't want it.
Instead of installing anything, you curl the hosted /mcp endpoint with the MCP-Protocol-Version 2025-06-18 header and the query "database is locked"; the response returns the Hermes state-database-lock lesson or a no_match with an intake call.
Outcome: Either you skip a known failure path or the gap gets recorded as an intake so the next contributor can document it.
Register a pseudonymous node over curl, run a dry-run preview so auto-redact strips secrets, then submit the four-part lesson; the same node lets you take on bench-core tasks and appear in contributor ranking.
Outcome: Your fix becomes searchable failure memory under a node ID rather than your real identity, and other agents skip the bug.
Use cases
- Search indexed failure lessons for common errors like pip install timeout or database is locked before debugging from scratch.
- Install the MCP endpoint into Claude Code or Cursor so your assistant searches shared failure memory before answering.
- Contribute a structured lesson documenting a bug fix so other agents skip that same failure path.
- Run search_knowledge.py offline to retrieve relevant lessons without internet access.
- Capture Node.js crash data with fatal-guard and submit tombstones to the network.
- Register a pseudonymous node and unlock lesson submission and risk checks.
- Give an agent the skill.md file so it searches first, solves, documents, and submits with consent.
- Join challenges and contributor ranking to build a verified contribution record.
Setup time & first value
How long it actually takes to get something useful out of MisakaNet — broken out by persona, not the marketing-page minute.
About 30 seconds for the hosted path: one npx command, a restart of clients that load MCP config at startup, and a `--verify` check. The curl route is instant with no install. Local search is a git clone plus `pip install misakanet-core`. Writing lessons takes longer — registration plus an admission step before submission unlocks.
Switching to or from MisakaNet
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a team wiki or Confluence postmortem page: port each write-up into the Problem / Root Cause / Fix / Verify lesson format and submit it via the MCP write tools.
- →From pasting errors into a general chat assistant: install the MCP endpoint with npx so the assistant searches lessons before answering.
- →From a local notes file of recurring build errors: clone the repo, run search_knowledge.py on each error, and submit lessons for the gaps that return no_match.
- ↗To a managed knowledge base: export lessons from the git repository, since the corpus is a plain clone away and Apache 2.0 licensed.
- ↗To semantic or vector retrieval over your own logs: keep the lesson text as seed documents, but plan your own embedding pipeline since MisakaNet retrieval is BM25.
- ↗To no tooling at all: run `npx @misaka-net/misakanet-setup --uninstall` to remove the MCP config from every assistant the installer wrote.
Integrations
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “MisakaNet”, and we withheld 6: 6 could not be judged, because “MisakaNet” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about MisakaNet.
Official links
What are the best MisakaNet alternatives?
The closest alternatives to MisakaNet we list are Hello Agents, AgentScope and Hermes Desktop. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Hello Agents | Free | Free | — |
| AgentScope | Free | Free | — |
| Hermes Desktop | Free | Free | — |
Alternatives to MisakaNet
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AgentScope
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Hermes Desktop
Hermes Desktop is a free, open-source desktop GUI for the Hermes Agent — a self-hosted AI agent with a built-in learning loop that turns
Tools that pair well with MisakaNet
Common stack mates teams adopt alongside MisakaNet, with the specific reason each pairing earns its keep.
Hello Agents
Free 16-chapter Datawhale open-source tutorial that teaches you to build AI agents from scratch in Python, including your own HelloAgents framework.
AgentScope
AgentScope is an open-source Python framework from Alibaba for building distributed multi-agent AI systems.
Hermes Desktop
Hermes Desktop is a free, open-source desktop GUI for the Hermes Agent — a self-hosted AI agent with a built-in learning loop that turns
MisakaNet vs its closest rival
MisakaNet's closest head-to-head is with Truleo — Truleo is the right choice if you're a law enforcement agency needing to streamline investigations and reduce report writing time with AI. MisakaNet is ideal for AI agent developers wanting a free, community-driven debugging knowledge base. They serve entirely different domains, so pick based on your role. Verdict generated
Head-to-head comparisons
Misakanet vs Truleo
Truleo is the right choice if you're a law enforcement agency needing to streamline investigations and reduce report writing time with AI. MisakaNet is ideal for AI agent developers wanting a free, community-driven debugging knowledge base. They serve entirely different domains, so pick based on your role.
GeneratedMisakanet vs Locus Robotics
These tools serve completely different domains. Locus Robotics is for high-volume warehouse automation requiring physical robots and ongoing subscription fees, ideal for 3PL and eCommerce operations. MisakaNet is a free, open-source knowledge-sharing tool for AI agents and developers, perfect for debugging recurrent errors without any hardware. Choose based on whether your problem is physical fulfillment (Locus) or software agent coordination (MisakaNet).
GeneratedMisakanet vs Presto Voice
MisakaNet and Presto Voice serve completely different domains. If you're an AI agent developer needing a free, open-source debugging knowledge base, MisakaNet is the clear choice. If you're a QSR chain aiming to automate drive-thru orders with proven revenue lift, Presto Voice is the established solution, especially with recent partnerships like Dairy Queen. Choose based on your industry and budget.
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