Is io.github.Deviank88/knowledge-rail safe to use?

io.github.Deviank88/knowledge-rail has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under Apache-2.0.

How do I install io.github.Deviank88/knowledge-rail?

io.github.Deviank88/knowledge-rail supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.

What can io.github.Deviank88/knowledge-rail do?

io.github.Deviank88/knowledge-rail provides 5 tools: knowledge_ingest, stdio, Requirements, Compatibility, License. See the full tools list on the server page for descriptions and parameters.

What AI clients work with io.github.Deviank88/knowledge-rail?

io.github.Deviank88/knowledge-rail is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.

Is io.github.Deviank88/knowledge-rail actively maintained?

io.github.Deviank88/knowledge-rail is actively maintained — last commit was 1 day ago.

io.github.Deviank88/knowledge-rail

knowledge-rail

Persistent, evidence-backed project knowledge and task context for coding agents.

2.3k/wk 5 tools GitHub npm

No known CVEs

Apache-2.0 license

Actively maintained

Last commit 1d ago

Works with most clients

Transport: stdio, sse, http

5 tools · ~277 tok

Grade A · 0.1% of 200K ctx

MCPpedia last refreshed this data 21h ago

Edit this pageView history

io.github.Deviank88/knowledge-rail is an MCP server that persistent, evidence-backed project knowledge and task context for coding agents. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 89/100 on MCPpedia's security, maintenance and efficiency rubric.

Other

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "knowledge-rail": {
      "args": [
        "-y",
        "knowledge-rail@2.0.2"
      ],
      "command": "npx"
    }
  }
}

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/io-github-deviank88-knowledge-rail)](https://mcppedia.org/s/io-github-deviank88-knowledge-rail)

Read me

What io.github.Deviank88/knowledge-rail does

KnowledgeRail is a local-first MCP server that turns project documentation and source code into durable, evidence-backed context for AI agents.

Test This Server

Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.

npx -y 'knowledge-rail' 2>&1 | head -1 && echo "✓ Server started successfully"

After testing, let us know if it worked:

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

89/100across 5 weighted dimensions

How we score →

0255075100

−11

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

Checked knowledge-rail against OSV.dev.

Inventory

Tools (5)

Click any tool to inspect its schema.

~277 tokens total

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is io.github.Deviank88/knowledge-rail safe to use?: io.github.Deviank88/knowledge-rail has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under Apache-2.0.
How do I install io.github.Deviank88/knowledge-rail?: io.github.Deviank88/knowledge-rail supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can io.github.Deviank88/knowledge-rail do?: io.github.Deviank88/knowledge-rail provides 5 tools: knowledge_ingest, stdio, Requirements, Compatibility, License. See the full tools list on the server page for descriptions and parameters.
What AI clients work with io.github.Deviank88/knowledge-rail?: io.github.Deviank88/knowledge-rail is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is io.github.Deviank88/knowledge-rail actively maintained?: io.github.Deviank88/knowledge-rail is actively maintained — last commit was 1 day ago.

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Community

Discussion

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Has anyone used this with Cursor?How do you handle auth?Any alternatives?

Edit this pageView history

Other

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "knowledge-rail": {
      "args": [
        "-y",
        "knowledge-rail@2.0.2"
      ],
      "command": "npx"
    }
  }
}

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/io-github-deviank88-knowledge-rail)](https://mcppedia.org/s/io-github-deviank88-knowledge-rail)

Read me

What io.github.Deviank88/knowledge-rail does

KnowledgeRail is a local-first MCP server that turns project documentation and source code into durable, evidence-backed context for AI agents.

Test This Server

Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.

npx -y 'knowledge-rail' 2>&1 | head -1 && echo "✓ Server started successfully"

After testing, let us know if it worked:

README

KnowledgeRail

KnowledgeRail is a local-first MCP server that turns project documentation and source code into durable, evidence-backed context for AI agents.

It is designed for agents that need to understand, change, review, or document a codebase without loading the whole repository into the model context. Retrieval is bounded, provenance is preserved, missing evidence is reported explicitly, and difficult queries widen progressively instead of silently losing relevant information.

Current status: stable release 2.6.2. The server uses MCP SDK 2.x and protocol 2026-07-28. It supports explicitly bound or safely inferred local stdio, a self-hosted loopback HTTP gateway, and a local desktop-chat adapter. KnowledgeRail operates no hosted service and does not upload project data. See SELF_HOSTING.md.

What it provides

Eight domain-oriented tools with validated actions and machine-readable next steps.
Task-aware hybrid retrieval with lexical, graph, passage, and optional semantic evidence.
Progressive widening with explicit coverage signals and GAP/unknown reporting.
Complete source ingestion through bounded segments, a coverage ledger, and durable Evidence IR.
A deterministic multi-language code index with symbol, reference, route, test, configuration, and database lookup.
Incremental graph, retrieval, and semantic indexes stored beside the project wiki.
Contract-driven Markdown deliverables with terminal review, content hashes, and optional caller-authored diagrams.
Conservative migration of existing v1/v2/v3 wikis and pre-rebrand .llm-wiki metadata.
Deterministic project binding through explicit Cursor workspace configuration, cwd-aware IDE processes, and terminal agents.
A local HTTP gateway that keeps concurrent clients and projects isolated per request.
A desktop-chat workspace catalog with opaque, expiring per-chat bindings.

KnowledgeRail does not call an LLM itself. The connected MCP client chooses and calls the tools. OCR and embeddings are optional external providers configured by the user.

Deterministic code-evidence languages

Code evidence is extracted locally without tree-sitter, native binaries, downloaded grammars, or runtime parser dependencies. Each file is owned by exactly one versioned adapter, so upgrading one language reparses only that language's files. Unsupported or deliberately skipped constructs remain visible through recorded raw-fallback demand rather than being assigned an unreliable anchor.

Adapter	Files	Indexed constructs
TypeScript / JavaScript / LWC	`.ts`, `.tsx`, `.mts`, `.cts`, `.js`, `.jsx`, `.mjs`, `.cjs`, `.js-meta.xml`	Classes, functions, methods, tests, routes, imports, calls, LWC decorators and component targets.
Java	`.java`	Classes, interfaces, enums, records, methods, Javadoc, JUnit markers, Spring routes, imports.
Kotlin	`.kt`, `.kts`	Classes, objects and companions, top-level/member/extension functions, properties, KDoc, JUnit/Kotest markers, Spring and literal Ktor routes.
Apex	`.cls`, `.trigger`	Classes, methods, tests, REST resources, trigger events, and static SOQL/SOSL object references.
Salesforce metadata	`.object-meta.xml`, `.field-meta.xml`, `.validationRule-meta.xml`, `.flow-meta.xml`, `.permissionset-meta.xml`	SFDX objects, fields, validation rules, flows, permission sets, formulas, calls, and Apex-compatible database references.
C#	`.cs`	Namespaces, types, methods, properties, XML docs, test attributes, ASP.NET controller and minimal-API routes; nested quoted strings inside interpolations are masked without losing following code.
Go	`.go`	Functions, receiver methods, structs/interfaces, Go doc comments, tests, imports, and common router calls.

... View full README on GitHub

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

89/100across 5 weighted dimensions

How we score →

0255075100

−11

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

Checked knowledge-rail against OSV.dev.

Inventory

Tools (5)

Click any tool to inspect its schema.

~277 tokens total

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is io.github.Deviank88/knowledge-rail safe to use?: io.github.Deviank88/knowledge-rail has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under Apache-2.0.
How do I install io.github.Deviank88/knowledge-rail?: io.github.Deviank88/knowledge-rail supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What can io.github.Deviank88/knowledge-rail do?: io.github.Deviank88/knowledge-rail provides 5 tools: knowledge_ingest, stdio, Requirements, Compatibility, License. See the full tools list on the server page for descriptions and parameters.
What AI clients work with io.github.Deviank88/knowledge-rail?: io.github.Deviank88/knowledge-rail is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is io.github.Deviank88/knowledge-rail actively maintained?: io.github.Deviank88/knowledge-rail is actively maintained — last commit was 1 day ago.