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Agent Toolkits

What are Toolkits?

Toolkits allow you to create focused groups of MCP servers that work together for specific tasks or workflows. Instead of connecting to all your available tools at once (which can confuse AI assistants), toolkits let you create targeted combinations optimized for particular use cases.

note

Why use toolkits? When AI assistants have access to too many tools at once, they can struggle to choose the right ones. Toolkits solve this by creating focused, task-specific tool groups.

Toolkits vs Skills

Toolkits and Skills are complementary but distinct. Understanding the difference prevents confusion when building agent workflows.

ToolkitSkill
What it isA set of tools (MCP servers)A set of instructions and business context
How it worksSwitch to itLoad on top of the current toolkit
PurposeDefines what tools are availableDefines how to use them
Replaces current context?YesNo — layers on top
Multiple active at once?NoYes
Example"Support" toolkit with Gmail + Slack"Escalation Procedures" skill

A Skill does not replace your toolkit — it adds domain knowledge and workflow instructions on top of whatever toolkit is currently active. Multiple Skills can be loaded simultaneously.

Skills

Learn how to create and load Skills for reusable AI capabilities

Civic toolkit interface showing organized tool groups
Organize your MCP tools into focused, task-specific groups

Common Toolkit Examples

Marketing Analytics

Tools: Google Analytics + Notion + Slack

Perfect for marketing teams who need to pull analytics data, document insights, and share reports with the team.

Developer Debugging

Tools: GitHub + PostgreSQL + Notion

Ideal for developers who need to investigate issues, query databases, and document solutions.

Content Creation

Tools: Linear + GitHub + Slack

Great for product teams managing feature requests, code reviews, and team communication.

Customer Support

Tools: Notion + HubSpot + Slack

Excellent for support teams who need to access customer data, update tickets, and coordinate responses.

How to Create a Toolkit

Creating a toolkit takes just a few steps and lets you build focused tool groups for your specific workflows.

  1. 1
    Create New Toolkit

    Click the "+ Create toolkit" button in the top navigation, next to your current toolkit name.

    Civic interface showing the Create toolkit button in the navigation
    Click 'Create toolkit' to start building your focused tool group
  2. 2
    Name Your Toolkit

    Give your toolkit a descriptive name and URL alias. This helps you and your team understand what the toolkit is designed for.

    Create New Toolkit dialog showing name and URL alias fields
    Enter a name and URL alias for your toolkit

    Example names:

    • "Marketing Redshift" (for marketing analytics)
    • "Debug Kit" (for development troubleshooting)
    • "Content Pipeline" (for content creation workflow)
  3. 3
    Copy Your Toolkit URL

    Once created, you'll get a unique URL for your toolkit that you can use in any MCP-compatible client.

    Toolkit setup page showing the unique MCP URL for the toolkit
    Copy your toolkit-specific MCP URL to use in AI clients

    Toolkit URL format:

    https://app.civic.com/hub/mcp?profile=your-toolkit-name

    Default URL (all tools):

    https://app.civic.com/hub/mcp

How to Delete a Toolkit

Method 1: Using chat

Ask in the chat for your toolkit to be deleted. For example:

Delete my development toolkit.

Method 2: Using the toolkits drop-down

Open the toolkits dropdown at the top of the page and click the gear icon. Delete buttons will appear next to each toolkit's name.

Nexus interface showing the Delete toolkit button in the navigation
Click on the gear icon in the toolkits dropdown to delete a toolkit

Using Toolkits in AI Clients

You have two main ways to work with toolkits:

Method 1: Direct URL Connection

Use your toolkit's specific URL when setting up MCP connections in clients like Claude Desktop, Cursor, or VS Code.

https://app.civic.com/hub/mcp?profile=marketing-redshift

This will connect your AI client to only the tools in that specific toolkit.

Method 2: Switch Toolkits in Civic UI

If you're using Civic Chat or managing multiple toolkits, you can switch between them using the dropdown in the Civic interface. Simply select the toolkit you want to use from the toolkit selector in the top navigation.

Toolkit Management

Adding Tools to a Toolkit

Navigate to your toolkit and click "Add Tools" to select from your connected services. You can add or remove tools anytime without affecting your AI client connections.

Editing Toolkit Names

Click on your toolkit name to edit it. The URL alias will update automatically, but existing connections will continue to work.

Sharing Toolkits

Toolkit URLs are tied to your account's authentication. Team members will need their own toolkit configurations, but you can share the concept and tool combinations. Toolkits cannot be shared between organizations. A tookit is linked to the organization where it was created.

Connecting the Same Service with Multiple Accounts

Each toolkit maintains its own set of authorizations. This means you can connect the same MCP server (for example, Slack) to multiple toolkits using different credentials — such as one toolkit for your own workspace and another for a client's workspace.

To connect the same service with different credentials across toolkits:

  1. Switch to the first toolkit using the toolkit selector in the top navigation.
  2. Add the MCP server for the service.
  3. Go to Authorizations, find the MCP you just installed and click on it. When it opens you will see a card that says Level: Authorization access level. Click the drop down and select Toolkit level.
  4. Complete the OAuth authorization flow. The credentials are stored against this toolkit only.
  5. Switch to your second toolkit and repeat steps 2-4 with the different account credentials.

Each toolkit stores its authorizations independently, so updating or revoking access in one toolkit does not affect the others.

Default vs Toolkit URLs
  • Default URL: Gives access to ALL your connected tools
  • Toolkit URL: Gives access to ONLY the tools in that specific toolkit
  • You can use both simultaneously in different AI clients
Filtering Tools in Toolkits

One of the most important factors in the accuracy of an LLM is the amount of tools it has access to. The more tools, the more likely it is that it will pick the wrong one.

Some MCP servers include a large number of tools, only a few of which may be relevant to your use case.

Narrow down your toolkit by asking the AI to filter tools based on usage or specific functionality. The filtered selection is saved to your toolkit.

Sample prompts:

  • "This toolkit has too many tools. Please select only the ones related to generating reports and store that against the toolkit"
  • "Please filter out any tools we did not use in this interaction, and store that against the toolkit"
Presetting Parameters

You can train the LLM to use tools the way you want them.

If a tool, or set of tools, includes a parameter, that you always want set to a specific value, you can prompt the LLM to preset it.

The AI will automatically use these presets when calling those tools. Presets act as hard overrides. The LLM cannot change them during tool execution.

Sample prompts:

  • "From now on, in this toolkit, always use property ID xyz when using Google Analytics"
  • "Preset the log groups parameter to this list: [log-group-1, log-group-2, log-group-3] when executing log queries"
  • "Always use the production database connection for queries in this toolkit"

Interpolated parameters

Interpolated parameters let you define a template with placeholders that the LLM fills in at call time. This constrains how the tool is used without exposing the full underlying parameter.

Syntax: Use ${variableName} as a placeholder in your template value. The system exposes variableName to the LLM instead of the original parameter.

Example — SQL query scoped to a specific table:

Preset the sql parameter of a Postgres tool to:

SELECT * FROM users WHERE email = '${email}'

The LLM now sees an email parameter instead of the raw sql parameter. It can only query the users table with that exact shape.

The escape field is required. It controls how the LLM-provided value is sanitized before interpolation:

ModeUse for
sqlValues inside single-quoted SQL strings
shellShell command arguments
pathFilenames within a fixed directory — strips ../ traversal
urlURL query parameter values
htmlHTML text content
alphanumericStrictest — only a-z A-Z 0-9 @ . - _
warning

Using the wrong escape mode does not provide adequate protection. When in doubt, use alphanumeric. The none mode applies no escaping and should only be used for trusted internal values.

Sample prompts:

  • "Please preset the Postgres execute_sql tool to get the total number of users from the users table with a given email domain"
  • "Preset the file read tool to only allow access to files inside /data/reports/ with a filename I provide"
Toolkit Descriptions

If you are building a toolkit for a very specific workflow or set of workflows, you can add useful context to the toolkit, and it will be provided to the context when connecting Civic.

Sample prompts:

  • "In this toolkit I will be checking for new issues from my incident manager, investigating in Github, and posting my findings to the project management service. Please set the toolkit description to summarise that process and provide instructions to the LLM when using it."
Aliasing Tools

Aliasing tools is useful if you have a specific workflow in mind, and helps improve tool selection accuracy by refining the tool name to match that description. For example, if you have a ticket manager and incident manager in the toolkit, you may have two "get-issue" tools - but you can rename one to "investigate-alert" and the other to "check-ticket".

note

This is particularly useful when combined with the preset parameter feature, to convert a generic tool to a targeted one.

Sample prompts:

  • Step 1: "Please preset the Google Analytics create-report tool with the following report parameters: ... and the following property id ..."
  • Step 2: "Please rename the create-report tool to 'get-24h-web-funnel-statistics'"
Cloning Tools

Clone a tool to give it another name, while keeping the original intact. This is useful when you want to create a specialized version of a tool without losing access to the generic one.

Sample prompts:

  • Step 1: "List all my calendars"
  • Step 2: "Please clone the list-events tool as 'list-my-events' and preset the calendar ID to my primary calendar"
Custom Tool Descriptions

Tool descriptions are determined by Civic and the MCP server providers, and provide only generic usage instructions to the LLM by default. Custom Descriptions combine with the other features to allow you to refine the tools to your specific use-case, by giving the LLM hints as to how you like to use the tools.

Sample prompts:

  • "Please update the slack get-messages tool description to look in the following channels: ..."

Best Practices

tip

Follow these guidelines to get the most out of your toolkits:

Keep Toolkits Focused

  • 3-5 tools maximum per toolkit for best AI performance
  • Choose tools that naturally work together for specific workflows
  • Remove tools you don't need by asking the LLM to filter them out

Use Descriptive Names

  • Good: "Customer Support Kit", "Marketing Analytics", "Dev Debug Tools"
  • Avoid: "My Tools", "Work Stuff", "Toolkit 1"

Organize by Workflow, Not by Service

  • Think workflow: "Content creation process" → Linear + GitHub + Slack
  • Don't think service: "All my productivity tools" → 15+ different services

Test Your Combinations

  • Try asking your AI to perform typical tasks with your toolkit
  • Adjust the tool combination if the AI seems confused or chooses wrong tools
  • Remove tools that don't add value to the specific workflow

Configure your Toolkit

  • Use broad toolkits to help figure out what you want, then bake the ones you need into a new toolkit
  • Ask the LLM to configure itself. Once you have a process that works well for you, ask it to create a new toolkit and configure the toolkit data to help the LLM to reproduce it

Stay Safe

  • Parameter presetting and tool filters can be used as guardrails
  • An LLM cannot use tools that you filter out, or override parameters you preset
  • For more fine-grained guardrails, ask the LLM which guardrails are available to it
  • Do not use descriptions as guardrails
  • Unlike tool filters and parameter presets, descriptions are guidelines only and LLMs can ignore them.

Guardrail execution order

When multiple guardrails are active, they run in ascending executionIndex order. The recommended convention is:

  • 0–999 — security constraints (run first to block or redact sensitive data)
  • 1000+ — response transforms / post-processors (run after constraints)

Order matters: redact sensitive fields before converting to CSV so redacted values don't leak into the output format.

Deleting a toolkit

When you delete a toolkit, its chat history is not lost — existing chats are reassigned to the default toolkit so they remain accessible. The default toolkit cannot be deleted.

Common Toolkit Patterns

Based on popular MCP server combinations, here are proven toolkit patterns:

Analytics & Reporting

Pattern: Data source + Documentation + Communication

Examples:

  • Google Analytics + Notion + Slack
  • PostgreSQL + Linear + GitHub
  • CoinGecko + Notion + Discord
Development Workflow

Pattern: Code repository + Database + Issue tracking

Examples:

  • GitHub + PostgreSQL + Linear
  • GitHub + Sentry + Notion
  • GitHub + HubSpot + Slack
Customer Operations

Pattern: CRM + Documentation + Communication

Examples:

  • HubSpot + Notion + Slack
  • ActiveCampaign + Linear + GitHub
  • Dropbox + HubSpot + Notion

Next Steps

  1. 1
    Plan Your Toolkit

    Identify a specific workflow or task you do regularly that involves 3-5 tools

  2. 2
    Create Your First Toolkit

    Follow the steps above to create a focused toolkit for that workflow

  3. 3
    Test and Refine

    Use your toolkit with your preferred AI assistant and adjust the tool combination as needed

  4. 4
    Create More Toolkits

    Build additional toolkits for other workflows once you've validated the first one

tip

Deploying an agent? If you're connecting an autonomous agent or automation platform, see the Installing into an agent guide for profile locking, skills, and other agent-specific configuration.

Need Help?

Join our developer community if you need assistance creating effective toolkits for your workflows