MCP Tools Reference

All 9 Lore MCP tools with parameters, descriptions, and usage examples.

Lore exposes 9 tools via MCP. They fall into three categories: simple query tools (fast, cheap), project briefs (living synthesis), and agentic tools (multi-step, higher cost).

search

Semantic search across the knowledge base. Returns source summaries with relevance scores.

Parameter	Type	Required	Description
`query`	string	Yes	Search query
`project`	string	No	Filter to specific project
`source_type`	string	No	Filter by source type (e.g. "meeting", "slack")
`content_type`	enum	No	Filter by content type (interview, meeting, conversation, document, note, analysis)
`limit`	number	No	Max results (default 10)
`include_archived`	boolean	No	Include archived projects (default false)
`mode`	enum	No	Search mode: hybrid (default), semantic, keyword, regex
`since`	string	No	Only sources after this date. Accepts ISO dates, relative shorthand (7d, 2w, 1m), or natural language ("last week")
`before`	string	No	Only sources before this date. Same formats as `since`
`sort`	enum	No	Sort order: relevance (default) or recent (newest first). Auto-set to recent for temporal queries

Search modes:

hybrid (default) — Combines vector similarity + full-text search via RRF fusion. Best for most queries.
semantic — Vector similarity only. Use for conceptual queries where exact terms don't matter.
keyword — Full-text search only. Use for exact terms, identifiers, or proper nouns.
regex — Pattern matching in local files.

Temporal awareness: Queries with temporal language ("latest", "most recent", "last week") automatically boost recent sources and sort by date. Use since/before for explicit date filtering.

get_source

Retrieve full details of a source document by ID.

Parameter	Type	Required	Description
`source_id`	string	Yes	ID of the source document
`include_content`	boolean	No	Include full original content (default false)

Use after search returns a relevant source_id and you need the full document.

list_sources

Browse all sources, optionally filtered by project or type.

Parameter	Type	Required	Description
`project`	string	No	Filter to specific project
`source_type`	string	No	Filter by source type
`content_type`	string	No	Filter by content type (e.g. "interview", "meeting", "document")
`include_logs`	boolean	No	Include log entries (default false)
`limit`	number	No	Max results (default 20)

list_projects

List all projects with source counts and latest activity dates. Takes no parameters.

get_brief

Get the living project brief — a continuously-updated synthesis of all knowledge in a project. Returns the current state, key evidence with citations, open questions, and project trajectory.

Parameter	Type	Required	Description
`project`	string	Yes	Project name
`include_history`	boolean	No	Include version history metadata (default false)

Start here when working on a project. The brief gives you immediate context without searching from scratch. Returns staleness info — if new sources have been added since the brief was generated, it tells you how many.

Briefs auto-update when new content is ingested into the project (with a 5-second debounce), so they stay current without manual intervention. You can also manually refresh via lore brief generate <project> in the CLI.

log

Log quick status updates, decisions, and progress notes. Log entries are searchable via search and included in project briefs. They are hidden from list_sources by default (pass include_logs: true to see them).

Parameter	Type	Required	Description
`message`	string	Yes*	Log message (required for `add`)
`project`	string	Yes	Project this belongs to
`action`	enum	No	Action: add (default), update, delete
`log_id`	string	No	Required for `update` and `delete` actions

Natural language examples (what you'd say to your AI):

"Log that we decided to use JWT for auth in the backend project"
"Add a log entry: finished the export module refactor"

ingest

Manage content in the knowledge base — add, update, or delete documents. Handles both full documents and short insights/decisions. This is how AI agents save knowledge from conversations — users can simply ask their AI to "save this to lore" or "remember this decision."

Parameter	Type	Required	Description
`action`	enum	No	Action: add (default), update, delete
`id`	string	No	Source ID (required for update and delete)
`content`	string	Yes*	Document content (required for add and update; ignored for delete)
`title`	string	No	Title (auto-generated from content if not provided)
`project`	string	Yes*	Project this belongs to (required for add)
`source_type`	string	No	Content category (meeting, slack, github-issue, etc.). Defaults to "document"
`date`	string	No	ISO date (defaults to now)
`participants`	string[]	No	People involved
`tags`	string[]	No	Tags for categorization
`source_url`	string	No	Original URL for citation linking
`source_name`	string	No	Human-readable origin label

Actions:

add (default) — Idempotent, content deduplicated by SHA256 hash. Short content (≤500 chars) skips LLM extraction for speed.
update — Requires id + content. Replaces content and re-embeds for search. Optionally updates title.
delete — Requires id. Soft-deletes the source (recoverable via lore docs restore in the CLI). Blocklists the content hash to prevent re-sync.

Ingesting into a project with an existing brief automatically triggers a brief refresh (debounced 5 seconds), keeping project briefs up to date.

Natural language examples (what you'd say to your AI):

"Save this architecture decision to lore under the backend project"
"Ingest these meeting notes — project is product, participants are Sarah and Mike"
"Remember that we chose JWT over sessions for mobile compatibility"
"Update that document with Chris's response" → ingest(action: "update", id: "...", content: "...")
"Delete that old draft from lore" → ingest(action: "delete", id: "...")

research

Start a comprehensive research job. An internal agent iteratively searches, reads sources, cross-references findings, and synthesizes a research package with citations.

Parameter	Type	Required	Description
`task`	string	Yes	Research task description
`project`	string	No	Focus research on specific project
`include_sources`	boolean	No	Include source references (default true)
`depth`	enum	No	Research depth: quick (~30-60s), standard (~1-2 min, default), deep (~4-8 min)

Async: Returns immediately with a job_id. Poll research_status to get results.

Depth control:

quick — 3-5 sources, ~30-60 seconds. Good for focused, specific questions.
standard (default) — 5-10 sources, ~1-2 minutes. Balanced thoroughness.
deep — Exhaustive search, ~4-8 minutes. Use for comprehensive audits or broad questions.

Cost: Makes multiple LLM calls internally. Use search for simple lookups.

research_status

Poll for research job results. Long-polls for up to 20 seconds before returning.

Parameter	Type	Required	Description
`job_id`	string	Yes	The job_id returned by `research`

Returns an activity array showing what the agent is doing (searches, sources read, reasoning). When status is "complete", the full research package is in result.