Anansi Data

xyz.anansidataPublished by anansidata.xyzOfficial publisherv1.1.0Updated Oct 24, 2026

Time-series nobody else archives: LLM price history, prediction markets, gas, perp funding.

VerifiedStreamable HTTPWeb executableFinanceData & AnalyticsAI & ML

Overview

AI-generated overview

A remote MCP server exposing archived time-series data — LLM token prices, prediction markets, gas, perp funding — with search, snapshots, history, movers and a

What you can do
Resolve fuzzy model or dataset names into exact identifiers, and full-text search across current dataset values to find which dataset holds a figure. Read current LLM token prices, context windows and recent price changes. Pull the latest snapshot of a whole dataset, the full time-series for one key, or field-level diffs across a dataset. Rank fastest-moving keys and flag statistical outliers by z-score. Get a one-call verdict on a single key combining latest value, velocity, peer rank and anomaly score. Query the complete paid LLM price-change archive or ask for a cheapest-model recommendation under price, context and modality constraints.
When to use it
Useful when you need historical or current market and pricing data that providers overwrite or do not archive, such as auditing LLM price changes, charting or backtesting a single series, or deciding which model to route to under cost constraints.
Requirements
A remote streamable HTTP endpoint; no local runtime, package, account or API key is declared. Paid tools are billed per call in USD via x402, which typically requires a compatible crypto wallet or payment setup.
Before you install
Most tools are paid per call (from $0.005 to $0.05 via x402), so repeated use spends money. Paid calls may require a wallet or payment credential. Data is a snapshot from the provider's last poll, so freshness and completeness are not guaranteed; anomaly results are flagged as unreliable on young datasets.

Installation

In SourceWeft

  1. Open Anansi Data in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/xyz.anansidata%2Fanansi-data/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "anansi-data": {
      "type": "http",
      "url": "https://anansidata.xyz/mcp"
    }
  }
}

Tools

12

anansi_price_current

FREE. Current per-token prices for LLMs as recorded at our last poll: usd_per_prompt_token and usd_per_completion_token (USD per single token, not per million), context window in tokens, and the observation timestamp (unix seconds). Use this to check what a model costs right now, or to compare a handful of models before routing. Do NOT use it to see how a price MOVED — it returns only the latest observation; use anansi_price_changes_recent (free) or anansi_price_history (paid). Input: model_id is a substring match, so 'gpt-5' matches every gpt-5 variant; resolve exact IDs with anansi_search.

Parameterslimitmodel_id

anansi_price_changes_recent

FREE. LLM price changes we observed in the last 7 days: per model, which field moved (prompt, completion, cache_read), the from/to values in USD per token, the percentage move, and the unix timestamp we detected it. Providers publish only their current catalogue and overwrite it silently, so this record exists nowhere upstream. Use it to detect that a model you depend on got cheaper, dearer, or vanished. Do NOT use it for windows longer than 7 days or more than 25 rows — it is capped; use anansi_price_changes (paid) for the full unwindowed history. Input: days is clamped to 7.

Parametersdayslimit

anansi_price_changes

PAID ($0.03 via x402). The COMPLETE observed price-change history for every tracked LLM, with no time window and no row cap: model, field, from/to in USD per token, percent move, and detection timestamp. Use it to audit a provider's pricing behaviour over the whole archive or to feed a cost model. Do NOT use it for a quick 'did anything change lately' check — anansi_price_changes_recent answers that free. Input: since is a unix timestamp; omit it for everything we hold.

Parameterssincepayment_header

anansi_price_advisor

PAID ($0.05 via x402). Answers 'which model should I route to' in one call: returns the cheapest models satisfying hard constraints on price, context window and modality, ranked by prompt price ascending, PLUS every price change and deprecation affecting those candidates in the window. Use it when choosing or re-validating a routing target. Do NOT use it merely to look up one model's price (anansi_price_current, free). Inputs: max_prompt_price in USD per token (e.g. 0.000001); min_context in tokens; modality is a substring of the modality string such as 'text' or 'image'.

Parameterslimitmodalitywindow_smin_contextpayment_headermax_prompt_price

anansi_data_latest

PAID ($0.005 via x402). Current state of every tracked key in one dataset, as recorded at our last poll, with provenance naming the source and licence. Use it for the newest snapshot of a whole dataset — prediction-market probabilities, gas by chain, perp funding, stablecoin pegs. Do NOT use it for LLM prices (anansi_price_current is free) and do NOT use it for change-over-time (anansi_data_changes). Input: dataset must be an exact name from anansi_search; key optionally narrows to one row.

Parameterskeydatasetrequiredpayment_header

anansi_data_history

PAID ($0.02 via x402). The full recorded time-series for ONE key in one dataset, oldest to newest, each row carrying its observation timestamp. Use it to chart or backtest a single series. Do NOT use it to compare many keys at once (anansi_data_latest returns them all for one moment) and do NOT expect history predating our first observation — the archive is days old and depth varies by dataset. Inputs: dataset and key exactly as returned by anansi_search; since is a unix timestamp.

Parameterskeyrequiredsincedatasetrequiredpayment_header

anansi_data_changes

PAID ($0.02 via x402). Field-level diffs across a whole dataset: for each key that changed, which field moved, its from and to values, and when. Use it to detect movement across many keys without pulling every series. Do NOT use it for LLM prices specifically — anansi_price_changes_recent is free and anansi_price_changes is the full version. Input: since is a unix timestamp; omit for the whole archive.

Parameterssincedatasetrequiredpayment_header

anansi_movers

PAID ($0.03 via x402). Velocity ranking: which keys in a dataset moved fastest on one numeric field over a window, returned as rate of change with the underlying from/to values. Use it to find what is moving without reading every series. Do NOT use it to judge whether a move is unusual for that key — that is anansi_anomalies. Inputs: field must be a numeric field present in the dataset; window_s is seconds.

Parametersfieldrequiredlimitdatasetrequiredwindow_spayment_header

anansi_anomalies

PAID ($0.05 via x402). Statistical outliers: keys whose latest move breaks their OWN historical baseline, returned with a z-score. Use it to separate a genuinely abnormal move from ordinary volatility. Do NOT use it to rank raw speed (anansi_movers) and treat results cautiously on a young dataset, where a short baseline inflates z-scores. Input: z_threshold defaults to 3.0.

Parametersfieldrequireddatasetrequiredz_thresholdpayment_header

anansi_verdict

PAID ($0.04 via x402). One-call composite for a single key: its latest value, its velocity, its rank against peers in the same dataset, and its anomaly z-score — the answer four separate calls would give. Use it when you have one specific key and want a verdict rather than raw series. Do NOT use it to survey many keys (anansi_movers) or to fetch a full series (anansi_data_history). Inputs: dataset, key and a numeric field, all exactly as named in the dataset.

Parameterskeyrequiredfieldrequireddatasetrequiredpayment_header

Version history

1
  1. v1.1.0LatestSep 16, 2026

Score

83% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts

    Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.

  • LicenseNot applicable

    A hosted service is used under its provider's terms, so no license is expected here. This check is left out of the percentage.