research-notes-mcp

Structures raw research notes into organized knowledge. Parses unstructured text into atomic claims, discovers thematic clusters, and surfaces contradictions and knowledge gaps.

Tools

5 MCP tools for note structuring and theme discovery

parse

Ingest raw research notes, splitting into atomic claims with source attribution.

cluster_themes

Group related claims into thematic clusters using semantic similarity.

find_contradictions

Detect conflicting claims across sources with evidence comparison.

extract_questions

Surface unanswered questions and knowledge gaps from parsed notes.

generate_output

Produce structured summaries, outlines, or briefing documents from clustered themes.

Workflow

From raw notes to structured knowledge

Parse Raw notes become atomic, attributed claims

Cluster Claims grouped into semantic themes

Contradict Conflicting evidence surfaced and compared

Question Knowledge gaps identified for further research

Output Structured documents generated from themes

Integration Points

Receives research output, feeds into logging and evaluation

research-agent-mcp

Upstream research pipeline providing raw extracted evidence and claims.

research-log-mcp

Citations from structured notes feed into bibliography generation.

evaluation-mcp (Evalla)

Quality scoring of structured outputs and theme coherence.

Additional Materials

Study materials coming soon.

Sibling

research-agent-mcp →

Sibling

research-log-mcp →

Prototype 01

Research Agent Suite →