radius-mcp-server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@radius-mcp-serversearch the docs for how to deploy a container"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
radius-mcp-server
A local MCP (Model Context Protocol) server that gives AI assistants everything they need to know about Radius:
Docs — full-text search and page reads over the official documentation (docs.radapp.io), sourced from a local cache of radius-project/docs.
Source — full-text search and file reads over radius-project/radius: Go source, architecture docs, design notes, specs, and TypeSpec/Bicep type definitions.
It needs no local setup: on first use it clones shallow, read-only caches of both repos for itself (see Data sources below).
Tools
Tool | Description |
| Full-text search over the Radius docs |
| Read one docs page (by URL, URL path, or slug) as clean markdown |
| Browse doc sections / list pages in a section |
| Refresh the local docs cache from GitHub |
| Full-text (or regex) search over the Radius source repo |
| Read a file from the Radius source repo |
| List a directory in the Radius source repo |
| Refresh the managed source cache from GitHub |
Related MCP server: directory-indexer
Quick start (once published to npm)
Most MCP clients just need to be told to run npx -y radius-mcp-server. See Connecting it to an MCP client for exact config per tool. Requires Node.js 18+ and git on PATH.
Data sources
Source | Local cache | |
Docs |
|
|
Source |
|
|
Both are shallow (--depth 1) clones made on first use and left in place across runs; call radius_docs_sync / radius_source_sync to pull the latest.
If you already have a local radius-project/radius checkout you'd rather use instead of a managed clone — e.g. you're working in it directly — point RADIUS_REPO_PATH at it (or run this server from a directory with a sibling radius/ folder, which is auto-detected). When set, that checkout is treated as yours to manage; radius_source_sync becomes a no-op and the tools just read from it as-is.
Connecting it to an MCP client
All of these assume the package is published; swap npx -y radius-mcp-server for node /absolute/path/to/radius-mcp-server/dist/index.js to point at a local build instead (see Development).
Claude Code
claude mcp add radius -- npx -y radius-mcp-serverOr add manually to .mcp.json (project-scoped) or ~/.claude.json (user-scoped):
{
"mcpServers": {
"radius": {
"command": "npx",
"args": ["-y", "radius-mcp-server"]
}
}
}Restart Claude Code (or run /mcp to check connection status) and the radius_* tools will be available.
Claude Desktop
Add the same block to your Claude Desktop config
(~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"radius": {
"command": "npx",
"args": ["-y", "radius-mcp-server"]
}
}
}Restart Claude Desktop to pick up the new server.
VS Code (GitHub Copilot Chat)
Add to .vscode/mcp.json in your workspace (or via "MCP: Open User Configuration" for a user-wide install). Note the top-level key is servers, not mcpServers:
{
"servers": {
"radius": {
"command": "npx",
"args": ["-y", "radius-mcp-server"]
}
}
}VS Code will prompt to start the server the first time it's used; check its status via the MCP Servers view.
GitHub Copilot coding agent
In the repository's Settings → Copilot → Coding agent → MCP configuration, add:
{
"mcpServers": {
"radius": {
"type": "local",
"command": "npx",
"args": ["-y", "radius-mcp-server"],
"tools": ["*"]
}
}
}type and tools are required by Copilot coding agent's schema (unlike the other clients above). See GitHub's MCP docs if you want to allowlist specific tools instead of ["*"].
Other clients (Cursor, Windsurf, ...)
Most other MCP-capable tools follow the same mcpServers convention as Claude Desktop above — check the client's docs for the exact config file location.
Publishing to npm
To publish a new version (maintainers only):
npm login # once, if not already logged in
npm run build # or rely on the prepublishOnly hook
npm version patch # or minor / major — bumps package.json + tags
npm publish # prepublishOnly runs the build automatically
git push --follow-tagsnpm publish is public and effectively permanent (npm blocks re-publishing a given version, and unpublishing after 72h is restricted) — double-check package.json's version and the tarball contents (npm pack --dry-run) before running it.
Development
npm install
npm run build # one-off build
npm run dev # tsc --watch
npm start # run the built server directly on stdio (Ctrl+C to stop)Re-run npm run build (or use npm run dev in the background) after editing anything in src/, then restart the server in your MCP client to pick up changes.
Available Tools
4 toolsradius_docs_syncRefresh the local Radius documentation cacheA
Pulls the latest changes from the radius-project/docs GitHub repo (the source of https://docs.radapp.io/) into the local cache. Call this if answers seem stale; otherwise the cache is reused as-is across calls.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It mentions pulling changes into cache, implying mutation, but does not disclose potential side effects (e.g., network usage, cache overwrite behavior, error handling). Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Front-loaded with action and condition. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simplicity (0 params, no output schema), description fully covers purpose, usage, and caching behavior. No missing context for agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, schema coverage 100%. Description adds no param info, which is expected. Baseline 4 for zero-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'Pulls' and resource 'local Radius documentation cache' from the specific GitHub repo. Distinguishes from sibling tools like radius_source_sync by specifying docs repo. Provides condition for use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to call ('if answers seem stale') and when not to ('otherwise the cache is reused as-is'), providing clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
radius_source_readRead a file from the Radius source repoA
Reads the full content of one file from a checkout of radius-project/radius by its path relative to the repo root, e.g. "pkg/recipes/engine/engine.go" or "docs/architecture/README.md".
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | File path relative to the repo root |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'reads' but does not disclose limitations like file size, encoding, or error behavior for missing paths. For a simple read operation, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action ('Reads the full content'), and contains zero superfluous words. Every part is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description covers the essential purpose and provides examples. Could mention return format or error cases, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'path' parameter with 100% coverage. The description adds concrete examples (e.g., 'pkg/recipes/engine/engine.go'), providing extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads a single file from the radius-project/radius repo by its path relative to the root, with concrete examples. This distinguishes it from siblings like radius_source_search (search) and radius_source_sync (sync).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (need file content) but does not explicitly state when not to use or mention alternatives. The sibling tool names provide context but are not referenced in the description itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
radius_source_searchSearch the Radius source repoA
Full-text search over a checkout of radius-project/radius: Go source (pkg/, cmd/), architecture docs and design notes (docs/architecture, eng/design-notes), specs, TypeSpec/Bicep type definitions, and more. If no local checkout is configured, this server clones a shallow copy itself on first use (may take a bit the first time). Use this for implementation details, resource-provider internals, or design rationale that isn't covered in the published docs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to return (default 10) | |
| query | Yes | Search terms, or a regex if useRegex is true, e.g. "func.*Recipe" | |
| useRegex | No | Treat query as a case-insensitive regular expression | |
| pathPrefix | No | Restrict to a subdirectory, e.g. "pkg/recipes" or "docs/architecture" |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that a shallow clone is made if no local checkout exists, and that first use may be slow. This sets appropriate expectations for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the core purpose, and adds essential context (clone behavior, use case) without redundancy or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no output schema, the description adequately explains the scope, setup behavior, and intended use cases. It could mention pagination or result format, but overall is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, meaning each parameter is already documented. The description does not add new semantic details for parameters beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies a clear verb 'search' and resource 'Radius source repo', listing specific directories covered. It distinguishes from sibling tools (radius_source_read, radius_source_sync, radius_docs_sync) by focusing on full-text search over source code and docs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: 'for implementation details, resource-provider internals, or design rationale that isn't covered in the published docs.' It also mentions the initial clone delay, but does not explicitly state when not to use or offer alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
radius_source_syncRefresh the local Radius source cacheA
Pulls the latest changes from radius-project/radius into this server's managed cache. Only applies when no external checkout was configured (RADIUS_REPO_PATH unset and no sibling radius/ directory); otherwise this is a no-op since your checkout is yours to manage.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description bears full responsibility. It discloses the no-op behavior under specific conditions and indicates it updates a local cache. While it could mention potential wait time or resource usage, the current disclosure is adequate for a simple cache refresh operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that front-load the main action ('Pulls the latest changes...') and then provide the key conditional. No extraneous words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with no output schema, the description sufficiently explains the core behavior and the no-op condition. It does not describe return values, but that is acceptable given the tool's simplicity. Slight room for improvement by noting what happens after sync (e.g., cache state).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the input schema is empty. With 100% schema coverage, the description adds no parameter details, but the baseline for 0 parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool refreshes the local cache by pulling latest changes from the radius-project/radius repository. The title reinforces this as 'Refresh the local Radius source cache'. This distinguishes it from sibling tools (radius_source_search, radius_source_read, radius_docs_sync) which are for searching, reading, or syncing docs, respectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (to refresh cache) and when not (when external checkout configured via RADIUS_REPO_PATH or sibling radius/ directory). The no-op condition is clearly described, helping the agent decide if calling this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool has a clearly distinct purpose: searching source code, reading a specific file, syncing source cache, and syncing docs cache. No overlap in functionality.
All tools follow a consistent 'radius_{source|docs}_{action}' pattern with snake_case. The verb 'sync' is used for both sync tools, maintaining uniformity.
Four tools is well-scoped for accessing source code and documentation. It covers search, read, and sync operations without unnecessary bloat.
The set covers search, read, and cache management, but lacks a directory listing tool. However, search can be used to find files by name, mitigating the gap.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Versioned documentation registry and semantic search for AI tools and coding assistants.
Ingest, manage, and retrieve documents for RAG-powered AI applications
Securely search and manage workspace context files for AI agents and teams.
Search and read Rust documentation for the standard library and any crate on crates.io
Related MCP Servers
- AlicenseAqualityDmaintenanceProvides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.7221MIT
- AlicenseNot gradedqualityCmaintenanceProvides AI assistants with semantic search and read access to local files and directories, enabling knowledge retrieval from indexed content.1516MIT
- AlicenseNot gradedqualityDmaintenanceProvides semantic search over markdown documentation using RAG, allowing natural language queries and integration with MCP clients.1MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to explore, search, and read codebase repositories and API specifications efficiently, with support for file searching, content search via ripgrep, and reading API specs.23ISC
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Alec13355/radius-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server