MCP reference
MCP resources and prompts
Use PrompTessor context resources and user-invoked prompt templates when the MCP client supports them.
Verified against the implementation ·
Resources
| Resource URI | Scope | Contents |
|---|---|---|
| promptessor://account/usage | usage:read | Unified account usage and public API policy |
| promptessor://history/optimizations/recent | history:read | The 10 most recent optimization history items |
| promptessor://library/community/recent | library:read | The first page of recent Community Prompts |
Resources return application/json text. The host decides how and when to attach resource contents to model context.
{
"jsonrpc": "2.0",
"id": 10,
"method": "resources/list",
"params": {}
}Authorization and limits
Reading a resource requires the scope listed above and consumes one read-rate-limit request, but no AI credit. Unauthorized, insufficient-scope, and rate-limit failures are returned as MCP protocol errors by the host.
Prompt templates
| Prompt | Arguments | Purpose |
|---|---|---|
| optimize-current-prompt | prompt; optional targetModel | Instruct the agent to call optimize_prompt with one variation and return the best result |
| generate-ready-to-use-prompt | goal; optional targetModel | Instruct the agent to call generate_prompt with outputMode ready_to_use |
Client support differs
A client may support tools while not exposing MCP prompts or resources in its interface. This does not mean the PrompTessor server failed to register them.
{
"jsonrpc": "2.0",
"id": 12,
"method": "prompts/list",
"params": {}
}Prompt templates do not run tools by themselves
prompts/get returns messages that instruct the host agent to call a PrompTessor tool. The host still decides whether to call it, asks for any required approval, and enforces the tool OAuth scope.