MCP Server | Dialogue API

The Dialogue MCP server exposes the corpus as tools that Claude Desktop — or any Model Context Protocol compatible client — can call directly during a conversation.

Setup

1. Get an API key

Contact ben@dialogue-ai.co to request access. You will receive a single API key.

2. Configure Claude Desktop

Add the following to your Claude Desktop config file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

1 {
2   "mcpServers": {
3     "dialogue": {
4       "command": "npx",
5       "args": ["-y", "@dialogue-ai/mcp"],
6       "env": {
7         "DIALOGUE_API_KEY": "your_api_key"
8       }
9     }
10   }
11 }

Restart Claude Desktop. You will see “dialogue” appear in the tools list.

Available tools

`get_corpus_overview`

Returns aggregate statistics for the full corpus: emotional register breakdown, life stage breakdown, top products mentioned, top behavioural signals, and top life events.

No parameters.

`search_comments`

Semantic search over the corpus using a natural language query. Returns the most relevant comments with their metadata and similarity score.

Parameter	Type	Required	Description
`query`	string	Yes	Natural language query, e.g. `"fear of redundancy affecting mortgage decisions"`
`limit`	integer	No	Number of results (1–50). Default: `10`
`threshold`	number	No	Minimum cosine similarity (0–1). Default: `0.4`
`emotional_register`	enum	No	Filter to a specific emotional tone
`life_stage`	enum	No	Filter to a specific life stage
`product`	string	No	Filter to comments mentioning a specific product

`get_quotes`

Retrieves high-engagement verbatim quotes sorted by like count. Use this to find the most resonant audience voice for a given segment.

Parameter	Type	Required	Description
`emotional_register`	enum	No	Filter by emotional tone
`life_stage`	enum	No	Filter by life stage
`life_event`	string	No	e.g. `partner_death`, `redundancy`, `first_home_purchase`
`product`	string	No	e.g. `life_insurance`, `pension_sipp`, `mortgage`
`min_likes`	integer	No	Minimum like count. Default: `0`
`limit`	integer	No	Number of results (1–50). Default: `10`

`filter_comments`

Returns a structured filtered slice of the corpus by any combination of emotional register, life stage, product, signal, or minimum like count. Use this for quantitative analysis or to pull raw comments for a specific segment.

Parameter	Type	Required	Description
`emotional_register`	string	No	Filter by emotional tone
`life_stage`	string	No	Filter by life stage
`product`	string	No	Filter by product mentioned
`signal`	string	No	e.g. `protection_gap_described`, `implicit_deliberator`
`min_likes`	integer	No	Minimum like count. Default: `0`
`limit`	integer	No	Results per page (1–100). Default: `20`
`offset`	integer	No	Pagination offset. Default: `0`

Example prompts

Once connected, you can ask Claude questions like:

“What are the most common fears UK adults have about retirement planning?”

“Find me five high-engagement quotes from pre-retirement users worried about their pension.”

“What financial products are mentioned most often by people who have recently lost a partner?”

“Give me a breakdown of the emotional register across first-home buyers.”