Verbaterm Policy Intelligence
Judged, citation-checked policy corpus over MCP. Keyless public reads; API key for AI tools.
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"verbaterm": {
"url": "https://verbaterm.com/mcp"
}
}
}Remote endpoints
https://verbaterm.com/mcpstreamable-httpWhat it can do
Tool inventory
Tools (7)
🟢search_policies(q, category, limit)
Search Verbaterm's judged, citation-checked public policy corpus (companies, products, policy kinds). Returns derived review metadata — findings counts, scores, freshness — never raw policy text.
Input Schema
{
"type": "object",
"properties": {
"q": {
"type": "string",
"description": "Company or product name to search."
},
"category": {
"type": "string",
"description": "Optional audience category slug."
},
"limit": {
"type": "number",
"description": "Max results (default 20, max 50)."
}
}
}🟢list_policies
List published public-library policy reviews available in the corpus.
Input Schema
{
"type": "object",
"properties": {}
}🟢get_policy_review(companySlug, productSlug, policyKind)
Get the full judged review for one published policy: findings with verbatim citation excerpts, scores, summary, and provenance. Cite the source URLs back to the user.
Input Schema
{
"type": "object",
"properties": {
"companySlug": {
"type": "string"
},
"productSlug": {
"type": "string"
},
"policyKind": {
"type": "string",
"description": "terms, privacy, cookies, data_processing, or other."
}
},
"required": [
"companySlug",
"productSlug",
"policyKind"
]
}🟢start_private_review(policyText, documentTitle, policyKind)
Start a private Verbaterm review of pasted policy text (requires a Verbaterm API key; debits the caller's plan allowance, not API credits). Returns a sessionId to poll with get_private_review_progress.
Input Schema
{
"type": "object",
"properties": {
"policyText": {
"type": "string",
"description": "Full pasted policy text (min 80 chars)."
},
"documentTitle": {
"type": "string"
},
"policyKind": {
"type": "string",
"description": "terms, privacy, cookies, data_processing, other, or auto."
}
},
"required": [
"policyText"
]
}🟢get_private_review_progress(sessionId)
Poll progress of a private review started with start_private_review.
Input Schema
{
"type": "object",
"properties": {
"sessionId": {
"type": "string"
}
},
"required": [
"sessionId"
]
}🟢get_private_review_result(sessionId)
Get the completed private review (findings + citations) for a session started with start_private_review. Raw source text is not returned.
Input Schema
{
"type": "object",
"properties": {
"sessionId": {
"type": "string"
}
},
"required": [
"sessionId"
]
}⚪ask_question(question, reviewRef)
Ask a citation-grounded follow-up question about a public library review or a private session (requires a Verbaterm API key; debits the caller's plan Q&A allowance).
Input Schema
{
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "3–1000 characters."
},
"reviewRef": {
"type": "object",
"description": "{ kind: \"public_path\", companySlug, productSlug, policyKind } or { kind: \"private\", sessionId }."
}
},
"required": [
"question",
"reviewRef"
]
}Community
Evidence