search

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If no MCP sources are connected:

To search across your tools, you'll need to connect at least one source.

Check your MCP settings to add ~~chat, ~~email, ~~cloud storage, or other tools.

Supported sources: ~~chat, ~~email, ~~cloud storage, ~~project tracker, ~~CRM, ~~knowledge base,

and any other MCP-connected service.

2. Parse the User's Query

Analyze the search query to understand:

• Intent: What is the user looking for? (a decision, a document, a person, a status update, a conversation)

• Entities: People, projects, teams, tools mentioned

• Time constraints: Recency signals ("this week", "last month", specific dates)

• Source hints: References to specific tools ("in ~~chat", "that email", "the doc")

• Filters: Extract explicit filters from the query:

• from: — Filter by sender/author

• in: — Filter by channel, folder, or location

• after: — Only results after this date

• before: — Only results before this date

• type: — Filter by content type (message, email, doc, thread, file)

3. Decompose into Sub-Queries

For each available source, create a targeted sub-query using that source's native search syntax:

~~chat:

• Use available search and read tools for your chat platform

• Translate filters: from: maps to sender, in: maps to channel/room, dates map to time range filters

• Use natural language queries for semantic search when appropriate

• Use keyword queries for exact matches

~~email:

• Use available email search tools

• Translate filters: from: maps to sender, dates map to time range filters

• Map type: to attachment filters or subject-line searches as appropriate

~~cloud storage:

• Use available file search tools

• Translate to file query syntax: name contains, full text contains, modified date, file type

• Consider both file names and content

~~project tracker:

• Use available task search or typeahead tools

• Map to task text search, assignee filters, date filters, project filters

~~CRM:

• Use available CRM query tools

• Search across Account, Contact, Opportunity, and other relevant objects

~~knowledge base:

• Use semantic search for conceptual questions

• Use keyword search for exact matches

4. Execute Searches in Parallel

Run all sub-queries simultaneously across available sources. Do not wait for one source before searching another.

For each source:

• Execute the translated query

• Capture results with metadata (timestamps, authors, links, source type)

• Note any sources that fail or return errors — do not let one failure block others

5. Rank and Deduplicate Results

Deduplication:

• Identify the same information appearing across sources (e.g., a decision discussed in ~~chat AND confirmed via email)

• Group related results together rather than showing duplicates

• Prefer the most authoritative or complete version

Ranking factors:

• Relevance: How well does the result match the query intent?

• Freshness: More recent results rank higher for status/decision queries

• Authority: Official docs > wiki > chat messages for factual questions; conversations > docs for "what did we discuss" queries

• Completeness: Results with more context rank higher

6. Present Unified Results

Format the response as a synthesized answer, not a raw list of results:

For factual/decision queries:

[Direct answer to the question]

Sources:

- [Source 1: brief description] (~~chat, #channel, date)

- [Source 2: brief description] (~~email, from person, date)

- [Source 3: brief description] (~~cloud storage, doc name, last modified)

For exploratory queries ("what do we know about X"):

[Synthesized summary combining information from all sources]

Found across:

- ~~chat: X relevant messages in Y channels

- ~~email: X relevant threads

- ~~cloud storage: X related documents

- [Other sources as applicable]

Key sources:

- [Most important source with link/reference]

- [Second most important source]

For "find" queries (looking for a specific thing):

[The thing they're looking for, with direct reference]

Also found:

- [Related items from other sources]

7. Handle Edge Cases

Ambiguous queries:

If the query could mean multiple things, ask one clarifying question before searching:

"API redesign" could refer to a few things. Are you looking for:

1. The REST API v2 redesign (Project Aurora)

2. The internal SDK API changes

3. Something else?

No results:

I couldn't find anything matching "[query]" across [list of sources searched].

Try:

- Broader terms (e.g., "database" instead of "PostgreSQL migration")

- Different time range (currently searching [time range])

- Checking if the relevant source is connected (currently searching: [sources])

Partial results (some sources failed):

[Results from successful sources]

Note: I couldn't reach [failed source(s)] during this search.

Results above are from [successful sources] only.

Notes

• Always search multiple sources in parallel — never sequentially

• Synthesize results into answers, do not just list raw search results

• Include source attribution so users can dig deeper

• Respect the user's filter syntax and apply it appropriately per source

• When a query mentions a specific person, search for their messages/docs/mentions across all sources

• For time-sensitive queries, prioritize recency in ranking

• If only one source is connected, still provide useful results from that source