dao-proposals-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_spacesB | |
| list_proposalsC | |
| get_proposal_detailsB | |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| summarize_proposals | Generate a prompt to summarize proposals for a given space. Parameters: space_id (str): The unique identifier of the Snapshot space. Returns: A list of prompt messages to guide the summarization process. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: get_proposal_details fetches details for a specific proposal, list_proposals lists recent proposals for a space, and list_spaces lists available spaces. There is no overlap in functionality, making it easy for an agent to select the right tool.
All tool names follow a consistent verb_noun pattern (get_proposal_details, list_proposals, list_spaces) using snake_case. The naming is predictable and readable, with no deviations in style or convention.
With only 3 tools, the server feels thin for a DAO proposals domain, as it lacks operations like creating, updating, or voting on proposals. While the tools cover basic read functions, the scope suggests more actions would be needed for full workflow support.
The toolset is severely incomplete for managing DAO proposals, as it only provides read operations (get and list) without any write capabilities such as creating, updating, deleting, or voting on proposals. This creates significant gaps that will hinder agent workflows in this domain.