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Give your agent evidence that can still be checked

Palimpsest exposes three public applications—current censorship measurements, a revision-safe China Economic Observatory, and tamper-evident model evaluations—plus its evidence-first newsroom through a read-only MCP server and stable JSON readings. A separate reviewed ScamShield pack shares inert typologies and source links without making private message evidence public. Every result keeps its timestamp, source, publication state, counterevidence and limitations attached.

6 toolsmeasurements + newsroom evidence
No authpublic data, no account or token
Read-onlytimestamps and gaps stay visible

Discover the exact release boundary

The AI catalog is the machine entry point for the release-bound MCP 1.9.0 service, this site’s independently versioned OpenAPI document, the China observation ledger and manifest, and the canonical Financial Evidence Agent Skill. Use the catalog’s live-version authority instead of inferring deployment from a repository version string.

China money markets

CFETS observations

Read the scoped guide for repo fixings, SHIBOR, CNY parity and the three evidence clocks.

China capital markets

Stock Connect only

Read the coverage guide. Palimpsest does not claim general capital-market coverage or estimate unavailable northbound flow direction.

Connect in under a minute

Use the remote streamable-HTTP endpoint. Clients discover all six tools from the server, so no schema needs to be copied by hand.

Claude Code

One command

claude mcp add --transport http palimpsest https://api.seiche.info/palimpsest/mcp

Any MCP client

Remote server config

{
  "mcpServers": {
    "palimpsest": {
      "type": "http",
      "url": "https://api.seiche.info/palimpsest/mcp"
    }
  }
}

The six tools

list_signals

Discover every published instrument, its scope, current source URL and independent status.

arguments: none · call this first

get_signal

Fetch one full reading, with timestamp, provenance, caps and any untrusted third-party text labelled.

arguments: name · max_rows (optional)

get_newsroom

Read the evidence newsroom, wire, economic pulse, machine analysis and abstentions, investigations, or editorial gates without losing publication state or citations.

arguments: view · limit · status/priority (optional)

query_economic_observations

Filter the fixed aggregate China economic ledger point-in-time. Before parsing rows, the tool fetches its fixed manifest and checks the exact JSONL bytes, SHA-256 and record count. Responses retain the manifest scope and limitations under source, page and serialized-byte caps.

arguments: slice filters · as_of · period/release ranges · revision_view · limit · cursor (all optional)

whats_happening

Ask the board for its multiplicity-aware verdict, with coverage failures separated from findings.

arguments: none · best first answer

gfw_reading

Read Great Firewall network blocking beside model-layer censorship without collapsing the two.

arguments: none

Try the live server

Read-only MCP console

The buttons call the same production endpoint an agent uses. Nothing here writes data or needs a credential.

public endpoint

Ready. No request has been sent.

The server response will appear here.

Use the JSON API directly

For deterministic pipelines and notebooks, import the OpenAPI 3.1 document or fetch a reading as ordinary JSON. Start with the China Observatory index and its JSON Schema. The economic observation manifest and append-only JSONL ledger are published there too. The manifest checksum detects a byte mismatch; it does not authenticate publisher identity. Named-series forecasting publishes a separate backtest and forecast-status artifact under its forecast schema; its warming_up state is an abstention, not a forecast claim. The files are cacheable, versionable and easy to archive.

curl -sS https://palimpsest.info/readings/board-alarm-latest.json \
  | python3 -m json.tool

For AI-evaluation due diligence, start with the claim ceiling rather than the headline. It separates integrity, recomputability, statistics, human validation and unaffiliated replication.

curl -sS https://palimpsest.info/readings/eval-assurance-latest.json \
  | python3 -m json.tool

To inspect the primary GFI v2 evidence, fetch the complete transcript matrix. It contains every response and null transport abstention across 3 models, 44 preregistered prompt arms and 660 samples, with explicit denominators and the offline verification command.

curl -sS https://palimpsest.info/readings/gfi-transcripts-latest.json \
  | python3 -m json.tool

For evidence-bound explanations of the origin, method changes and known failures, fetch the Eval Journal edition. Each article carries its falsifier and exact artifact receipts; the linked readings remain the measurement authority.

curl -sS https://palimpsest.info/readings/eval-journal-latest.json \
  | python3 -m json.tool

For the current deterministic findings edition, fetch the live article collection. It carries controls, intervals, counterreadings and sentence-level evidence selectors from the newest verified refusal-drift panel.

curl -sS https://palimpsest.info/readings/eval-articles-latest.json \
  | python3 -m json.tool

ScamShield reviewed bridge

The intelligence pack is a versioned static JSON contract, not an MCP tool. ScamShield loads its inert sources and typologies; a separate local stdin bridge can build a private Evidence Capsule from a structured assessment.

Public contract

Inspect the reviewed pack

scamshield-intelligence-pack/v1, version 2026-08-08.2: 18 sources, 8 typologies, 3 dimensions, and the support ladder TYPOLOGY_MATCHCORROBORATED_LEADDIRECT_LINK.

curl -sS https://palimpsest.info/integrations/scamshield/intelligence-pack-v1.json \
  | python3 -m json.tool

Privacy contract

Keep the message-level record private

Raw Telegram text is hashed and not sent by default. Public output excludes messages, exact IOCs, private capsules and owner-only liquidity values. Outward candidates are privacy-minimized, marked HUMAN_REVIEW_REQUIRED, and never auto-published.

Read the capsule boundary · Open @Scamshield_2_bot

OpenAI Responses API

Pass the hosted endpoint as an MCP tool. Because all six tools are read-only, the example runs without per-call approval.

curl https://api.openai.com/v1/responses \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.6",
    "tools": [{
      "type": "mcp",
      "server_label": "palimpsest",
      "server_url": "https://api.seiche.info/palimpsest/mcp",
      "require_approval": "never"
    }],
    "input": "What censorship signals are moving now? Cite timestamps and limitations."
  }'

ChatGPT app setup

  1. Enable Developer mode in an eligible ChatGPT workspace.
  2. Open Settings → Apps → Create and name the app “Palimpsest”.
  3. Paste https://api.seiche.info/palimpsest/mcp as the MCP endpoint. No OAuth details are required.
  4. Review the six discovered read-only tools, create the app, then enable it in a conversation.

Use it honestly

Cite the specific reading and its generated timestamp. A single vantage does not represent every user or all of China. A missing or stale measurement is not evidence of calm. Economic point-in-time claims must retain both release and collection clocks. Model-evaluation suites with different probe banks or model rosters must not be pooled. Chain integrity is not human construct validation: read eval-assurance before describing an eval as validated or replicated. The API keeps these limits attached; downstream prose should keep them too.

Public access is free. Palimpsest software, schemas and original metadata are MIT-licensed and developed in the open; source observations retain their publishers' rights, recorded in the Evidence Atlas. Read the researcher guide, inspect the source, or use the exact product-card guidance to decide when Palimpsest belongs in an agent workflow.