Source Management logo

Source Management

OrganizationPopular
anthropics
source-management

Manages connected MCP sources for enterprise search. Detects available sources, guides users to connect new ones, handles source priority ordering, and manages rate limiting awareness.

Overview

Publisheranthropics
Repositoryknowledge-work-plugins
Skill namesource-management
Stars
24.9K
Forks
3K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by anthropics on GitHub. Read the source before you install it.

Installation

Install the Source Management AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anthropics/knowledge-work-plugins.git /tmp/knowledge-work-plugins
mkdir -p .claude/skills
cp -r /tmp/knowledge-work-plugins/enterprise-search/skills/source-management .claude/skills/source-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Source Management in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Source Management on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Source Management is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Source Management

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Knows what sources are available, helps connect new ones, and manages how sources are queried.

Checking Available Sources

Determine which MCP sources are connected by checking available tools. Each source corresponds to a set of MCP tools:

SourceKey capabilities
~~chatSearch messages, read channels and threads
~~emailSearch messages, read individual emails
~~cloud storageSearch files, fetch document contents
~~project trackerSearch tasks, typeahead search
~~CRMQuery records (accounts, contacts, opportunities)
~~knowledge baseSemantic search, keyword search

If a tool prefix is available, the source is connected and searchable.

Guiding Users to Connect Sources

When a user searches but has few or no sources connected:

You currently have [N] source(s) connected: [list].

To expand your search, you can connect additional sources in your MCP settings:
- ~~chat — messages, threads, channels
- ~~email — emails, conversations, attachments
- ~~cloud storage — docs, sheets, slides
- ~~project tracker — tasks, projects, milestones
- ~~CRM — accounts, contacts, opportunities
- ~~knowledge base — wiki pages, knowledge base articles

The more sources you connect, the more complete your search results.

When a user asks about a specific tool that is not connected:

[Tool name] isn't currently connected. To add it:
1. Open your MCP settings
2. Add the [tool] MCP server configuration
3. Authenticate when prompted

Once connected, it will be automatically included in future searches.

Source Priority Ordering

Different query types benefit from searching certain sources first. Use these priorities to weight results, not to skip sources:

By Query Type

Decision queries ("What did we decide..."):

1. ~~chat (conversations where decisions happen)
2. ~~email (decision confirmations, announcements)
3. ~~cloud storage (meeting notes, decision logs)
4. Wiki (if decisions are documented)
5. Task tracker (if decisions are captured in tasks)

Status queries ("What's the status of..."):

1. Task tracker (~~project tracker — authoritative status)
2. ~~chat (real-time discussion)
3. ~~cloud storage (status docs, reports)
4. ~~email (status update emails)
5. Wiki (project pages)

Document queries ("Where's the doc for..."):

1. ~~cloud storage (primary doc storage)
2. Wiki / ~~knowledge base (knowledge base)
3. ~~email (docs shared via email)
4. ~~chat (docs shared in channels)
5. Task tracker (docs linked to tasks)

People queries ("Who works on..." / "Who knows about..."):

1. ~~chat (message authors, channel members)
2. Task tracker (task assignees)
3. ~~cloud storage (doc authors, collaborators)
4. ~~CRM (account owners, contacts)
5. ~~email (email participants)

Factual/Policy queries ("What's our policy on..."):

1. Wiki / ~~knowledge base (official documentation)
2. ~~cloud storage (policy docs, handbooks)
3. ~~email (policy announcements)
4. ~~chat (policy discussions)

Default Priority (General Queries)

When query type is unclear:

1. ~~chat (highest volume, most real-time)
2. ~~email (formal communications)
3. ~~cloud storage (documents and files)
4. Wiki / ~~knowledge base (structured knowledge)
5. Task tracker (work items)
6. CRM (customer data)

Rate Limiting Awareness

MCP sources may have rate limits. Handle them gracefully:

Detection

Rate limit responses typically appear as:

  • HTTP 429 responses
  • Error messages mentioning "rate limit", "too many requests", or "quota exceeded"
  • Throttled or delayed responses

Handling

When a source is rate limited:

  1. Do not retry immediately — respect the limit
  2. Continue with other sources — do not block the entire search
  3. Inform the user:
Note: [Source] is temporarily rate limited. Results below are from
[other sources]. You can retry in a few minutes to include [source].
  1. For digests — if rate limited mid-scan, note which time range was covered before the limit hit

Prevention

  • Avoid unnecessary API calls — check if the source is likely to have relevant results before querying
  • Use targeted queries over broad scans when possible
  • For digests, batch requests where the API supports it
  • Cache awareness: if a search was just run, avoid re-running the same query immediately

Source Health

Track source availability during a session:

Source Status:
  ~~chat:        ✓ Available
  ~~email:        ✓ Available
  ~~cloud storage:  ✓ Available
  ~~project tracker:        ✗ Not connected
  ~~CRM:   ✗ Not connected
  ~~knowledge base:      ⚠ Rate limited (retry in 2 min)

When reporting search results, include which sources were searched so the user knows the scope of the answer.

Adding Custom Sources

The enterprise search plugin works with any MCP-connected source. As new MCP servers become available, they can be added to the .mcp.json configuration. The search and digest commands will automatically detect and include new sources based on available tools.

To add a new source:

  1. Add the MCP server configuration to .mcp.json
  2. Authenticate if required
  3. The source will be included in subsequent searches automatically

Frequently asked questions

What does the Source Management AI skill do?

Manages connected MCP sources for enterprise search. Detects available sources, guides users to connect new ones, handles source priority ordering, and manages rate limiting awareness.

Why use Source Management on TypingMind?

Because you install it once and use it with any model. Source Management is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Source Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/knowledge-work-plugins/tree/main/enterprise-search/skills/source-management. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Source Management?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Source Management?

As many as you like. As long as a model supports skills, you can use Source Management with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Source Management AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇