Feason Context
Source-grounded Christian evidence for AI agents, with passage provenance, tradition attribution, coverage boundaries, and citation verification.
Hosted MCP Server
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Documentation
Feason Context · REST API 1.3
Christian context API.Ready for your model.
Give an AI application inspectable Scripture, historical sources, named theological perspectives, and citations it can verify. Feason retrieves the evidence. Your product decides how to use it.
Contextualize endpoint https://www.feason.com/api/context/v1/contextualize
Explore the platform
One context layer.Every way to use it.
Start with the job your product needs to do. Every path uses the same versioned Christian source corpus, stable citations, tradition attribution, and explicit coverage boundaries.
01
Ground answers
Christian AI grounding
Turn a question into model-ready context drawn from Scripture, creeds, councils, historical theology, and named Christian traditions.
Contextualize Search
02
Test assertions
Theological claim checking
Separate supporting, contradicting, qualifying, contextual, and unclassified evidence without treating silence as disagreement.
Evaluate claim Claim proof
03
Research deeply
Evidence discovery
Search exact passages or assemble a structured research packet with positions, provenance, historical context, caveats, and confidence.
Search Evidence packet
04
Show your work
Citation integrity
Verify quotations against an immutable release and expose the corpus version behind every answer your application produces.
Verify citation Manifest
05
Prove issuance
Signed proof verification
Authenticate a complete claim graph with Ed25519, a separately published trust key, and an append-only Merkle-log receipt.
Signed envelope Transparency receipt
Choose your connection
From first request to production.
- REST API Five-minute guided quickstart
- MCP Context tools for compatible agents
- Developer atlas Anonymous MCP and REST call activity
- TypeScript Typed client and response models
- Python Synchronous and async client
- OpenAPI 3.1 Portable machine-readable contract
- Proof verifier Issuer and transparency verification
- API access Scoped, read-only developer keys
Decision guides
Choose the evidence layer before the model.
Compare product categories by source identity, provenance, coverage, verification, and the work your team still owns.
Feason Context vs. generic theology RAG
Compare corpus ownership, provenance, tradition coverage, citation verification, and operational responsibility.
APIs for grounding Christian AI
Choose among Scripture text, source search, theological evidence, and current-web APIs by evidence contract.
Bible API vs. theological evidence API
Separate canonical reading needs from historical, doctrinal, and tradition-aware research needs.
Verify theological AI citations
Resolve, compare, contextualize, and audit quotations before an AI-generated answer is published.
Quickstart
One call.Grounded context.
Send the user’s question with a prompt budget. The response’s context field can be placed directly before the question in your model input. Citation metadata remains separate and inspectable.
- The key is scoped to read-only canonical context.
- The response never claims that missing coverage means a tradition has no teaching.
- Disputed positions stay attributed to their source or tradition.
Request POST /contextualize
curl https://www.feason.com/api/context/v1/contextualize \
-H "Authorization: Bearer $FEASON_CONTEXT_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"query": "How did early Christians speak about grace?",
"traditions": ["catholic", "orthodox", "reformed"],
"maxTokens": 2000,
"maxSources": 12
}'
Response application/json
{
"corpusVersion": "theology-v7.0.0",
"context": "# Feason Context\n...",
"citations": [{ "label": "E1", "passageId": "..." }],
"coverage": {
"representedTraditions": ["catholic", "orthodox"],
"missingTraditions": ["reformed"]
},
"usage": { "estimatedTokens": 1842, "truncated": false }
}
Claim checking
Test a claim.Keep the nuance.
Feason matches the wording to a curated claim definition, retrieves relevant passages, and groups only human-annotated stances. Your interface can show the evidence behind each category instead of presenting an unexplained verdict.
- Supporting and contradicting passages remain inspectable.
- Qualifying evidence stays distinct from opposition.
- Silence, missing retrieval, and unclassified passages never become negative proof.
Request POST /evaluate-claim
curl https://www.feason.com/api/context/v1/evaluate-claim \
-H "Authorization: Bearer $FEASON_CONTEXT_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"claim": "Children of believers may be baptized.",
"limitPerStance": 5
}'
Response shape application/json
{
"normalizedClaim": "infants-may-be-baptized",
"supportingEvidence": [],
"contradictingEvidence": [{ "passageId": "..." }],
"qualifyingEvidence": [{ "passageId": "..." }],
"contextualEvidence": [],
"unclassifiedEvidence": [],
"confidence": 0.92,
"negativeEvidencePolicy": "Only explicitly opposing annotations..."
}
REST surface
Seven operations with clear jobs.
All operations use bearer authentication, concrete JSON contracts, per-client limits, and the same immutable Context corpus behind Feason’s MCP server.
POST /api/context/v1/contextualize
Build model-ready context
One call returns a token-budgeted evidence block, stable citation labels, and explicit tradition coverage.
POST /api/context/v1/evaluate-claim
Check a theological claim
Group retrieved passages by curated stance, with explicit caveats and no false negative inference from silence.
POST /api/context/v1/claim-proof
Build a claim proof
Commit exact evidence, disclosed rules, validation checks, and a bounded result to an unsigned SHA-256 Merkle root.
POST /api/context/v1/search
Search exact passages
Run lexical, semantic, or hybrid retrieval over the versioned corpus with source and tradition filters.
POST /api/context/v1/evidence-packet
Assemble research evidence
Retrieve Scripture, primary sources, historical context, positions, provenance, caveats, and confidence.
POST /api/context/v1/verify-citation
Verify a quotation
Check a passage or exact quote against an immutable corpus release snapshot.
GET /api/context/v1/manifest
Inspect the active release
Read the active corpus version, source counts, relationships, claims, and verification distribution.
Developer access
Create a scoped key.
Self-service keys can read only the shared canonical corpus. Access to a member’s private study context uses OAuth and explicit consent instead.
Checking your Feason session…
Product boundary
Evidence in. Verdicts out.
Feason improves what a model can inspect without claiming that retrieval itself settles interpretation.
Source-first
Every included passage carries a stable ID, reference, provenance URL, license, and verification status.
Tradition-aware
Differences are named and sourced. Missing corpus coverage remains visible instead of becoming synthetic consensus.
Prompt-bounded
The context block respects the requested budget and reports when evidence was omitted or shortened.
Questions
Christian Context API FAQ.
What developers need to know before grounding an AI product in Christian sources.
What is a Christian context API?
A Christian context API retrieves relevant Scripture and theological sources for an application. Feason returns exact passages, provenance, citations, named tradition coverage, and explicit caveats so AI-generated answers can be inspected.
Can Feason Context be used with any AI model?
Yes. The REST API returns provider-neutral JSON and prompt-ready Markdown. Applications can use the context with OpenAI, Anthropic, Google, open-source, or other language models.
Does the API favor one Christian denomination?
No. Feason is non-denominational and source-grounded. Disputed views are attributed to their sources and traditions, while missing corpus coverage is reported instead of treated as absence of teaching.
How do developers authenticate?
Signed-in Feason members can create scoped, read-only developer keys. Each key expires after 90 days, can be revoked, and cannot access a member’s private study context.