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Author MCP server

by litheonhq·io.github.litheonhq/author-mcp-server·v0.1.1
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Recall, check, search, timeline, and graph tools for fiction writers via Seizn Memory v3.

B75/100grade B
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Safety scan
B75/100

full report

Adoption
New

0 stars26 downloads/wk

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Author tools (6)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • seizn_author_check

    Check a passage of prose for canon conflicts (character contradictions, timeline issues, broken promises, rule violations). Returns conflicts with severity (P1 critical, P2 warning, P3 stylistic) and rationale. Use this on a finished scene before committing to draft.

  • seizn_author_graph

    Return a relationship graph subset rooted at a given entity. Includes direct ties (1-hop) and indirect (2-hop) with edge kinds (rival, ally, family, etc). Use for character-relationship questions like "who is Seoyun connected to".

  • seizn_author_recall

    Recall canon facts for a named entity (character / location / object / rule / promise / event). Returns the canonical name, last 3 mentions with chapter snippets, current state, and any pending conflicts. Use this when the user asks about a name they wrote earlier and may have forgotten.

  • seizn_author_remember

    Approve a fact as canon for an existing entity. Use when the user confirms an AI-suggested fact ("yes Seoyun is a reporter as of Ch.4") or when adding a new canonical fact mid-conversation. The fact becomes the source of truth for future recall and conflict checks.

  • seizn_author_search

    Semantic search across all entities in a project. Use when the user asks about a concept rather than a specific name (e.g. "what happens at the temple in chapters 3-7", "characters with grief arcs"). Returns entities ranked by semantic relevance.

  • seizn_author_timeline

    Return chapter-by-chapter beats for the project, optionally filtered by chapter range. Use when the user asks "what happened between Ch.5 and Ch.7" or needs to see story progression.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings
  • Code scan11 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 48 days ago12/15
  • Maintainer identityregistry namespace matches repository owner6/10
Overall 75/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Author compares

Against every graded Web search MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
75/100
higher than 45% of 3,470 Web search servers
Tools
6
the typical Web search server has 5
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
Downloads a week
26
more than 12% of 827 Web search servers with a package

What its tools let an agent do: 6 read

Install Author in Claude Code, Cursor or VS Code

Runs npx -y @seizn/author-mcp-server on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add author-mcp-server -- npx -y @seizn/author-mcp-server
Add to Cursor

What the publisher says

From the Author repository's README, as published. We do not edit it. Read it on GitHub

Seizn

Seize your memories. Seizn is the memory layer for AI characters, agents, and creative IP systems.

This README is written as the repo-level orientation file for human and AI operators. After reading only this file, another agent should understand what Seizn is, where the product is pivoting, how the codebase is organized, and which commands and guardrails matter.

Current Product Thesis

Seizn is not an LLM, not a vector database, and not a generic chatbot shell. It is a stateful memory operating layer around AI applications.

The core product stores, retrieves, governs, and explains long-lived context:

  • memories: facts, preferences, events, instructions, experiences, relationships
  • profile/persona state: stable user, character, or agent traits
  • graph state: entities, relationships, provenance, external IDs, observations
  • retrieval context: hybrid search, RAG, reranking, answer contracts, traceable evidence
  • runtime controls: replay, budget controls, policy checks, retention, audit logs, webhooks

The current strategy is a hybrid wedge:

  • Seizn Author: authoring memory for serial fiction, VN, TRPG, manga, drama rooms, and IP builders. This is the 2026-05 candidate direction. The KNOT integration is the first dogfood and PMF test.
  • Seizn Live: runtime memory middleware for game NPCs and AI characters. This is the 2026-04 NPC memory pivot and remains valid.

The unifying wedge is:

Build IP and character memory in an authoring surface, then export the same memory graph into a game or agent runtime.

The product should not be positioned as "a better memory API" in the abstract. The sharper pitch is:

  • memory layer for IP builders
  • AI memory layer for serial fiction
  • persistent memory for AI NPCs
  • replayable, governable, debuggable memory for AI systems

Why This Pivot Exists

The first pivot narrowed Seizn toward game NPC memory middleware. The reasoning was that Inworld, Convai, NVIDIA ACE, and similar stacks are strong at dialogue, voice, and expression, but long-lived memory and relationship persistence remain thin.

The 2026-05 candidate pivot adds an authoring angle. While working on KNOT, the useful stack became clear:

Seizn memory + persona/profile + world/relationship graph

That same stack is valuable before runtime, while writers and IP builders are designing characters, relationships, episodes, and continuity. The market may be broader and faster to test than game studio middleware alone.

Current decision state:

  • Do not treat Seizn Author as a completed full pivot yet.
  • Use KNOT as the first dogfood loop.
  • If the authoring workflow gives strong signal, build a Seizn Author web surface and test with a small beta group.
  • If signal is weak, keep Author as an internal KNOT tool and continue Seizn Live for games.
  • Core assets survive either path: SDK, MCP, Graph, Profile, memory search, replay, governance.

Differentiation

Do not sell Seizn as "better semantic search." That is commodity in 2026.

The stronger differentiation is:

The roadmap filter for new features is:

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Author: common questions

Is Author MCP server safe?
Mostly: it is graded B (75/100). Read the Author safety report
How do I install Author?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Author need an API key?
Yes. The registry entry asks for SEIZN_API_KEY.
Is Author maintained?
The last commit was 86 days ago (2026-08-10). The latest release is v0.1.1.
What can I use instead of Author?
Servers from other publishers that do the same job: Link MCP server, Shodh Memory MCP server and Reverie MCP server.
How does Author compare with other Web search MCP servers?
safety score 75/100 (higher than 45% of 3,470 Web search servers); tools 6 (the typical Web search server has 5); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

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