Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add boshi-xixixi/TraeSkill --skill mcp-create-declarative-agentgit clone --depth 1 https://github.com/boshi-xixixi/TraeSkillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/boshi-xixixi/traeskill/mcp-create-declarative-agent)<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/mcp-create-declarative-agent"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/mcp-create-declarative-agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/mcp-create-declarative-agent"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/mcp-create-declarative-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.01996 |
| Opus 5 | $0.00010 | $0.00998 |
| Sonnet 5 | $0.00004 | $0.00399 |
| Haiku 4.5 | $0.00002 | $0.00200 |
Grade A, and why
mcp-create-declarative-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
---
mode: 'agent'
tools: ['changes', 'search/codebase', 'edit/editFiles', 'problems']
description: 'Create a declarative agent for Microsoft 365 Copilot by integrating an MCP server with authentication, tool selection, and configuration'
model: 'gpt-4.1'
tags: [mcp, m365-copilot, declarative-agent, model-context-protocol, api-plugin]
---
# Create MCP-based Declarative Agent for Microsoft 365 Copilot
Create a complete declarative agent for Microsoft 365 Copilot that integrates with a Model Context Protocol (MCP) server to access external systems and data.
## Requirements
Generate the following project structure using Microsoft 365 Agents Toolkit:
### Project Setup
1. **Scaffold declarative agent** via Agents Toolkit
2. **Add MCP action** pointing to MCP server
3. **Select tools** to import from MCP server
4. **Configure authentication** (OAuth 2.0 or SSO)
5. **Review generated files** (manifest.json, ai-plugin.json, declarativeAgent.json)
### Key Files Generated
**appPackage/manifest.json** - Teams app manifest with plugin reference:
```json
{
"$schema": "https://developer.microsoft.com/json-schemas/teams/vDevPreview/MicrosoftTeams.schema.json",
"manifestVersion": "devPreview",
"version": "1.0.0",
"id": "...",
"developer": {
"name": "...",
"websiteUrl": "...",
"privacyUrl": "...",
"termsOfUseUrl": "..."
},
"name": {
"short": "Agent Name",
"full": "Full Agent Name"
},
"description": {
"short": "Short description",
"full": "Full description"
},
"copilotAgents": {
"declarativeAgents": [
{
"id": "declarativeAgent",
"file": "declarativeAgent.json"
}
]
}
}
```
**appPackage/declarativeAgent.json** - Agent definition:
```json
{
"$schema": "https://aka.ms/json-schemas/copilot/declarative-agent/v1.0/schema.json",
"version": "v1.0",
"name": "Agent Name",
"description": "Agent description",
"instructions": "You are an assistant that helps with [specific domain]. Use the available tools to [capabilities].",
"capabilities": [
{
"name": "WebSearch",
"websites": [
{
"url": "https://learn.microsoft.com"
}
]
},
{
"name": "MCP",
"file": "ai-plugin.json"
}
]
}
```
**appPackage/ai-plugin.json** - MCP plugin manifest:
```json
{
"schema_version": "v2.1",
"name_for_human": "Service Name",
"description_for_human": "Description for users",
"description_for_model": "Description for AI model",
"contact_email": "[email protected]",
"namespace": "serviceName",
"capabilities": {
"conversation_starters": [
{
"text": "Example query 1"
}
]
},
"functions": [
{
"name": "functionName",
"description": "Function description",
"capabilities": {
"response_semantics": {
"data_path": "$",
"properties": {
"title": "$.title",
"subtitle": "$.description"
}
}
}
}
],
"runtimes": [
{
"type": "MCP",
"spec": {
"url": "https://api.service.com/mcp/"
},
"run_for_functions": ["functionName"],
"auth": {
"type": "OAuthPluginVault",
"reference_id": "${{OAUTH_REFERENCE_ID}}"
}
}
]
}
```
**/.vscode/mcp.json** - MCP server configuration:
```json
{
"serverUrl": "https://api.service.com/mcp/",
"pluginFilePath": "appPackage/ai-plugin.json"
}
```
## MCP Server Integration
### Supported MCP Endpoints
The MCP server must provide:
- **Server metadata** endpoint
- **Tools listing** endpoint (exposes available functions)
- **Tool execution** endpoint (handles function calls)
### Tool Selection
When importing from MCP:
1. Fetch available tools from server
2. Select specific tools to include (for security/simplicity)
3. Tool definitions are auto-generated in ai-plugin.json
### Authentication Types
**OAuth 2.0 (Static Registration)**
```json
"auth": {
"type": "OAuthPluginVault",
"reference_id": "${{OAUTH_REFERENCE_ID}}",
"authorization_url": "https://auth.service.com/authorize",
"client_id": "${{CLIENT_ID}}",
"client_secret": "${{CLIENT_SECRET}}",
"scope": "read write"
}
```
**Single Sign-On (SSO)**
```json
"auth": {
"type": "SSO"
}
```
## Response Semantics
### Define Data Mapping
Use `response_semantics` to extract relevant fields from API responses:
```json
"capabilities": {
"response_semantics": {
"data_path": "$.results",
"properties": {
"title": "$.name",
"subtitle": "$.description",
"url": "$.link"
}
}
}
```
### Add Adaptive Cards (Optional)
See the `mcp-create-adaptive-cards` prompt for adding visual card templates.
## Environment Configuration
Create `.env.local` or `.env.dev` for credentials:
```env
OAUTH_REFERENCE_ID=your-oauth-reference-id
CLIENT_ID=your-client-id
CLIENT_SECRET=your-client-secret
```
## Testing & Deployment
### Local Testing
1. **Provision** agent in Agents Toolkit
2. **Start debugging** to sideload in Teams
3. Test in Microsoft 365 Copilot at https://m365.cloud.microsoft/chat
4. Authenticate when prompted
5. Query the agent using natural language
### Validation
- Verify tool imports in ai-plugin.json
- Check authentication configuration
- Test each exposed function
- Validate response data mapping
## Best Practices
### Tool Design
- **Focused functions**: Each tool should do one thing well
- **Clear descriptions**: Help the model understand when to use each tool
- **Minimal scoping**: Only import tools the agent needs
- **Descriptive names**: Use action-oriented function names
### Security
- **Use OAuth 2.0** for production scenarios
- **Store secrets** in environment variables
- **Validate inputs** on the MCP server side
- **Limit scopes** to minimum required permissions
- **Use reference IDs** for OAuth registration
### Instructions
- **Be specific** about the agent's purpose and capabilities
- **Define behavior** for both successful and error scenarios
- **Reference tools** explicitly in instructions when applicable
- **Set expectations** for users about what the agent can/cannot do
### Performance
- **Cache responses** when appropriate on MCP server
- **Batch operations** where possible
- **Set timeouts** for long-running operations
- **Paginate results** for large datasets
## Common MCP Server Examples
### GitHub MCP Server
```
URL: https://api.githubcopilot.com/mcp/
Tools: search_repositories, search_users, get_repository
Auth: OAuth 2.0
```
### Jira MCP Server
```
URL: https://your-domain.atlassian.net/mcp/
Tools: search_issues, create_issue, update_issue
Auth: OAuth 2.0
```
### Custom Service
```
URL: https://api.your-service.com/mcp/
Tools: Custom tools exposed by your service
Auth: OAuth 2.0 or SSO
```
## Workflow
Ask the user:
1. What MCP server are you integrating with (URL)?
2. What tools should be exposed to Copilot?
3. What authentication method does the server support?
4. What should the agent's primary purpose be?
5. Do you need response semantics or Adaptive Cards?
Then generate:
- Complete appPackage/ structure (manifest.json, declarativeAgent.json, ai-plugin.json)
- mcp.json configuration
- .env.local template
- Provisioning and testing instructions
## Troubleshooting
### MCP Server Not Responding
- Verify server URL is correct
- Check network connectivity
- Validate MCP server implements required endpoints
### Authentication Fails
- Verify OAuth credentials are correct
- Check reference ID matches registration
- Confirm scopes are requested properly
- Test OAuth flow independently
### Tools Not Appearing
- Ensure mcp.json points to correct server
- Verify tools were selected during import
- Check ai-plugin.json has correct function definitions
- Re-fetch actions from MCP if server changed
### Agent Not Understanding Queries
- Review instructions in declarativeAgent.json
- Check function descriptions are clear
- Verify response_semantics extract correct data
- Test with more specific queries
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 316 lines · 20 tokens per session scan A 8aa6694de0da
mcp-create-declarative-agent is a skill published in the GitHub repository boshi-xixixi/TraeSkill (263 stars, last pushed 4mo ago), licensed MIT. It adds 20 tokens to every session and 1,996 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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