✦ Feason

Feason Context · MCP 7.0

Christian context
your AI can inspect.

Feason is a context layer for AI agents—not another chatbot. It gives developer tools structured access to source-grounded Scripture and theological research, verifiable citations, named tradition perspectives, and permissioned study memory.

Connect an AI clientUse the REST API
Remote MCP endpointhttps://www.feason.com/api/mcp

Detailed overview

One MCP server.
Three clear layers.

Feason separates shared evidence, personal context, and durable research so an agent can use each without confusing one for another.
01

Canonical context

Search a versioned corpus of Scripture, creeds, councils, patristic writing, historical theology, and confessional sources. Results preserve source, passage, edition, translation, license, URL, and verification metadata.

02

Private study context

With explicit permission, an agent can retrieve a user’s saved passages, notes, reading history, study progress, lecture notes, plans, and authored reflections. Personal data stays separate from canonical ranking.

03

Research workspace

Create private projects, save immutable evidence packets, curate exact passages, compare packet history, export citations, fork an inquiry, and create revocable read-only shares.

How it works

From tool call
to traceable evidence.

The model can reason over the response, but Feason controls retrieval, permissions, evidence boundaries, and provenance.
  1. 01

    The agent chooses a named tool

    Instead of asking a model to recall theology from training, the client calls a specific Feason tool such as search_sources, compare_traditions, or build_evidence_packet.

  2. 02

    Feason enforces the boundary

    OAuth and client credentials determine which public corpus and private user scopes are available. Read, write, sharing, and destructive actions remain distinct.

  3. 03

    Retrieval finds stored evidence

    Lexical and semantic search, metadata filters, curated relationships, and source-aware reranking locate exact passages. Missing coverage stays visible rather than being filled with generated text.

  4. 04

    The agent receives structured context

    Responses return evidence in labeled fields with stable IDs, provenance, caveats, confidence, and citation data so the client can display, verify, or continue working with it.

39 purpose-built tools

What developers can build with it.

Each capability is exposed as a typed MCP tool with a bounded job. Clients can combine them into research, study, writing, and verification workflows.

Find

Search exact sources

Search stored passages in lexical, semantic, or hybrid mode; filter by source type and metadata; fetch a source by stable ID; or expand a passage into its immediate stored context.
search_sourcesget_sourceget_passage_context

Understand

Build Scripture context

Retrieve an exact passage alongside literary context, corpus-derived cross-references, concepts, patristic commentary, and conciliar material—kept in separate fields.
get_scripture_contextget_primary_sources

Trace

Follow concepts and terms

Trace curated links among Scripture, theologians, councils, controversies, doctrines, and passages. Look up Greek and Latin forms, transliterations, variants, glosses, and translation cautions.
trace_conceptlookup_theological_term

Compare

Preserve real differences

Compare explicitly attributed tradition positions and separate consensus, disagreement, and missing coverage. Evaluate a proposition against curated supporting, contradicting, qualifying, and contextual evidence.
compare_traditionsevaluate_claim

Verify

Resolve and check citations

Resolve abbreviated references to exact passages, verify quotations or hashes against an immutable release snapshot, and format stored metadata as SBL, Chicago, BibTeX, or CSL-JSON.
resolve_citationverify_citationformat_citation

Assemble

Build evidence packets

Return one machine-readable packet containing primary sources, Scripture, historical context, concepts, attributed positions, passage-level provenance, caveats, and confidence.
build_evidence_packet

Remember

Continue a private study

With user-approved scopes, search personal study context and continue from saved passages, notes, progress, plans, and authored reflections without allowing that data to rewrite canonical results.
search_personal_contextcontinue_studyget_study_progress

Research

Run a durable project

Save evidence immutably, pin or exclude passages, annotate findings, export the project, fork a line of inquiry, and manage revocable read-only shares.
save_research_evidencecurate_research_evidenceexport_research_project

Example workflow

Ask for evidence,
not a verdict.

A client can ask Feason to assemble the relevant material, then let its own model analyze the structured response. Feason does not publish a final theological judgment on the model’s behalf.

  • A study assistant that quotes a passage only after verifying it against a fixed corpus release.
  • A research agent that builds and exports an evidence packet with inspectable source trails.
  • A writing tool that compares named traditions without erasing disagreement or inventing consensus.
  • A learning app that resumes a user’s study from authorized history while preserving the private/canonical boundary.
Tool callbuild_evidence_packet
{
  "question": "How did early sources discuss this doctrine?",
  "traditions": ["catholic", "orthodox", "reformed"],
  "limit": 12
}
Response anatomy
{
  "primarySources": [...],
  "scripture": [...],
  "historicalContext": [...],
  "positions": [...],
  "provenance": {...},
  "caveats": [...],
  "confidence": {...}
}

Designed for responsible use

The trust model is part of the product.

Feason is designed to make an agent’s evidence easier to inspect while limiting what the integration can access and what the system retains.

Evidence stays attributable

Stored passages carry their source provenance. Curated relationships and generated summaries are not presented as source text.

Traditions stay named

Comparisons attribute positions and expose disagreement or missing corpus coverage instead of collapsing them into a single answer.

Access stays scoped

OAuth consent and revocable client credentials gate private sources. An integration receives only the scopes a user grants.

Private stays separate

Journal titles and bodies are client-side encrypted and cannot be decrypted or searched by MCP. Other private context never changes canonical ranking.

Operations stay auditable

Feason records tool outcome, client, duration, and request identifiers for reliability and abuse prevention—not full requests, access tokens, or query text.

Quality stays measurable

Corpus coverage, citation accuracy, source drift, retrieval health, conformance, latency, failures, and human review are monitored as separate signals.

Connect

Use Feason from the AI client you already work in.

The same remote endpoint works across compatible MCP clients. Private tools trigger Feason’s scoped authorization flow.

Connect

Codex

Add the remote HTTP server to your Codex configuration. Feason opens OAuth when a requested tool needs private data.
[mcp_servers.feason]
url = "https://www.feason.com/api/mcp"

Connect

Claude

Add a custom remote MCP connector, enter the endpoint, and approve only the Feason scopes your workflow needs.
https://www.feason.com/api/mcp

Connect

ChatGPT

Create a custom MCP connector with the endpoint, then complete the Feason authorization and consent flow.
https://www.feason.com/api/mcp

Public evidence tools use the canonical corpus boundary.

Private tools require a signed-in Feason account and the relevant read or write scope.

Manage connected apps →