About OpenAkashic
OpenAkashic is a public library of methods and reported experience for people and agents. Its current module links methods to sources and dated reports, while retrieval is experimental and does not establish that a method will improve results.
Key features
- 01Browse source-linked methods
- 02Inspect reported results and failures
- 03View a clickable record graph
- 04Compare exact-version application reports
Use cases
- 01Explore methods for a work situation
- 02Review evidence and known limitations
- 03Record and compare applications of a method
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://knowledge.openakashic.com/mcp/claude mcp add --transport http szara7678-openakashic https://knowledge.openakashic.com/mcp/{"mcpServers":{"szara7678-openakashic":{"type":"http","url":"https://knowledge.openakashic.com/mcp/"}}}Open in Cursor{"servers":{"szara7678-openakashic":{"type":"http","url":"https://knowledge.openakashic.com/mcp/"}}}Open in VS Code{"mcpServers":{"szara7678-openakashic":{"type":"http","url":"https://knowledge.openakashic.com/mcp/"}}}{"mcpServers":{"szara7678-openakashic":{"serverUrl":"https://knowledge.openakashic.com/mcp/"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://knowledge.openakashic.com/mcp/Auth requiredTools
35| Parameter | Type | Required | Description |
|---|---|---|---|
| kind | any | No | Filter by note kind: 'capsule', 'claim', 'evidence', 'reference', 'playbook', etc. |
| tags | any | No | Filter by tags — only notes containing ALL specified tags are returned. Example: ['python', 'benchmark'] |
| limit | integer | No | Max number of results to return (default 8) |
| query | string | Yes | Search terms in plain language. Example: 'Python performance benchmark' |
| include_related | boolean | No | When true, depth-1 neighbors of top results are returned as context_neighbors. |
Details
From the project READMEOpenAkashic
A public library of methods and reported experience for people and agents.
Given a situation and goal, discover a method, inspect its conditions and sources, then attach what happened and discuss alternatives. The current direction is contextual know-how reuse, including open-ended work such as design, product experiments and career exploration.
- Try the public method library
- See measured results and known failures
- Run, test and contribute to the current module
- Dated reproducible evidence
The current portable implementation lives in public-methods/. It includes source-linked methods, public browsing, a clickable record graph, exact-version application reports, and an agent client. No API key is needed for public reads or local lexical browsing. Public demo writes remain disabled; self-hosted writes use a private operator credential.
Experimental: retrieval is candidate discovery, not expert endorsement or proof that the method solves the task. On 16 cross-domain development queries, hybrid retrieval found the intended first method 16/16, while on an earlier out-of-scope technical set it failed to abstain in 4/4 cases. Actual answer-quality improvement, human preference and same-quality billed-token savings are not established. Read the full results, not only a positive headline.
Closed Akashic personal memory and Open Time Machine are separate services. Private vaults, retired Samsung news data, credentials and operational databases are not part of this module. Older directories, installers, MCP claims and historical benchmarks elsewhere in this repository remain legacy material; they are not evidence of the current service's capabilities. Use the current module's instructions rather than old automatic installers.
Code license: Apache-2.0. Linked third-party originals retain their own rights; attribution and fixture scope.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.